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حرية الوصول المقاله
1 - الگوریتم تعیین دسته تولید محصول و توالی عملیات n کار روی m ماشین
رسول حجی هوشنگ تقی زادهدر این مقاله یک الگوریتم هیوریستیک با هدف تعیین مقدار بهترین دستۀ تولیدی جهت کمینه سازی زمان کل سیستم تولیدیبه منظور برآوردن تقاضای یک دوره معین برای یک محصول ارائه گردیده است. این الگوریتم با در نظر گرفتن زمان استاندارد عملیات،تعداد قطعات یکسان به کار رفته در یک واحد م أکثردر این مقاله یک الگوریتم هیوریستیک با هدف تعیین مقدار بهترین دستۀ تولیدی جهت کمینه سازی زمان کل سیستم تولیدیبه منظور برآوردن تقاضای یک دوره معین برای یک محصول ارائه گردیده است. این الگوریتم با در نظر گرفتن زمان استاندارد عملیات،تعداد قطعات یکسان به کار رفته در یک واحد محصول، زمان آماد هسازی ماشی نآلات، درصد ضایعات هر یک از عملیات روی ماشینمربوطه، و مقدار دسته تولیدی، زمان لازم برای انجام هر یک از عملیات مورد نیاز جهت تولید همان دسته تولیدی را محاسبه می کند.این الگوریتم با استفاده از اطلاعات محاسبه شده، قاعده SPTشروط تعیین شده در الگوریتم و مقدار تولید در هر دسته تولید،عملیات مورد نیاز برای تولید کل تقاضای یک دوره معین را به ماشین آلات تخصیص می دهد. سپس با توجه به مقدار این دسته تولید،مجموع زمان های آماده سازی و بیکاری ماشین آلات برای کل تقاضای دوره محاسبه می گردد. آنگاه با محاسبه مجموع این زمان ها برایمقادیر مختلف دسته های تولید و مقایسه آنها مقدار دسته تولید بهینه که مجموع این زمان ها را کمینه می سازد، به دست می آید. برایمقایسه این الگوریتم با الگوریتم های "هو و چانگ" ,"جانسون" , "پالمر"مثالهایی ارائه شده است. نتایج نشان می دهد که اینالگوریتم در مقایسه با الگوریتم های فوق، زمان کل بهتری را ارائه می دهد. تفاصيل المقالة -
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2 - رویکردی نوین جهت چیدمان منابع در شرایط نا مشخص بودن توالی پدیده ها
دکتر محمد تقی تقوی فرد حمید رضا دهنار صیدیدر این مقاله رویکردی نوین جهت مرتب کردن زمانی منابع و نیز کاربردهای آن ارائه می شود . اگر توالی پدیده ها معین و قابلکنترل نباشد، مبحث ترتیب گذاری و زمانبندی به تصمیم گیری در شرایط تناقض و حالت عدم اطمینان کامل گرهمی خورد ، که در اینجا برای نخستین بار در مدل های زمانبند أکثردر این مقاله رویکردی نوین جهت مرتب کردن زمانی منابع و نیز کاربردهای آن ارائه می شود . اگر توالی پدیده ها معین و قابلکنترل نباشد، مبحث ترتیب گذاری و زمانبندی به تصمیم گیری در شرایط تناقض و حالت عدم اطمینان کامل گرهمی خورد ، که در اینجا برای نخستین بار در مدل های زمانبندی و توالی عملیات طرح گردیده است . مدل هایی که در اینشرایط ایجاد می شوند، مدل های محتاطانه نامید ه شده و روش کلی حل آنها و نیز برای چیدمان ثابت منابع یک برنام ة زمانیکلی بنابر معیار بدبینانه برای انواع مسائل ارائه شده است . در این مقاله، الگوریتم پاد ایکرزxبرای تعیین چیدمان یکسانپدیده ها در محیطn × mبا هدف بیشینه سازیFmaxارائه می گردد. سپس پیچیدگی حل مدل های محتاطانه بررسی ومثالی کاربردی از مدل های محتاطانه مطرح و از طریق برنام ة زمانی ارائه شده و به کمک الگوریتم پاد ایکرزxحل و سپسحل آن توسط روش کلی نیز بررسی می شود . در انتها روایی و پایایی الگوریتم پاد ایکرزxمورد آزمون قرار گرفته ونتیجه گیری می گردد که : مسائل مربوطه از طریق نظریة بازی باید حل شوند و شیوة پیشنهادی قادر است ، این مسائل شدیداً سخت غیر خطی"را بطور صحیح و در مدت زمان مناسب حل نماید. تفاصيل المقالة -
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3 - TASA: A New Task Scheduling Algorithm in Cloud Computing
Somayeh Taherian Dehkordi Vahid Khatibi BardsiriCloud computing refers to services that run in a distributed network and are accessible through common internet protocols. It merges a lot of physical resources and offers them to users as services according to service level agreement. Therefore, resource management alo أکثرCloud computing refers to services that run in a distributed network and are accessible through common internet protocols. It merges a lot of physical resources and offers them to users as services according to service level agreement. Therefore, resource management alongside with task scheduling has direct influence on cloud networks’ performance and efficiency. Presenting a proper scheduling method can lead to efficiency of resources by decreasing response time and costs. This paper studies the existing approaches of task scheduling and resource allocation in cloud infrastructures and assessment of their advantages and disadvantages. Afterwards, a compound algorithm is presented in order to allocate tasks to resources properly and decrease runtime. The proposed algorithm is built according to conditions of compounding Min-min and Sufferage algorithms. In the proposed algorithm, task allocation between machines takes place alternatively and with continuous change of scheduling algorithms. The main idea of the proposed algorithm is to concentrate on the number of tasks instead of the existing resources. The simulation results reveal that the proposed algorithm can achieve higher performance in decreasing response time. تفاصيل المقالة -
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4 - Improving the palbimm scheduling algorithm for fault tolerance in cloud computing
Minoo SoltanshahiCloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud أکثرCloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud environment. Scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of suitable resources and assignment of workflows to them. Given the factors affecting their efficiency, these algorithms try to use resources optimally and increase the efficiency of this environment. The palbimm algorithm provides a scheduling method that meets the majority of the requirements of this environment and its users. In this article, we improved the efficiency of the algorithm by adding fault tolerance capability to it. Since this capability is used in parallel with task scheduling, it has no negative impact on the makespan. This is supported by simulation results in CloudSim environment. تفاصيل المقالة -
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5 - Data Replication-Based Scheduling in Cloud Computing Environment
Bahareh Rahmati Amir Masoud Rahmani Ali RezaeiAbstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable a أکثرAbstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes a bottleneck for the whole cloud workflow system and decreases the performance of the system dramatically. Job scheduling and data replication are two important techniques which can enhance the performance of data-intensive applications. It is wise to integrate these techniques into one framework for achieving a single objective. In this paper, we integrate data replication and job scheduling with the aim of reducing response time by reduction of data access time in cloud computing environment. This is called data replication-based scheduling (DRBS). Simulation results show the effectiveness of our algorithm in comparison with well-known algorithms such as random and round-robin. تفاصيل المقالة -
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6 - Task Scheduling Algorithm Using Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in Cloud Computing
Ghazaal Emadi Amir Masoud Rahmani Hamed ShahhoseiniThe cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user's jobs has emerged as an important challenge in the field of cloud computing. It is main أکثرThe cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user's jobs has emerged as an important challenge in the field of cloud computing. It is mainly due to several reasons, including ever-increasing advancements of information technology and an increase of applications and user needs for these applications with high quality, as well as, the popularity of cloud computing among user and rapidly growth of them during recent years. This research presents the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an evolutionary algorithm in the field of optimization for tasks scheduling in the cloud computing environment. The findings indicate that presented algorithm, led to a reduction in execution time of all tasks, compared to SPT, LPT, and RLPT algorithms.Keywords: Cloud Computing, Task Scheduling, Virtual Machines (VMs), Covariance Matrix Adaptation Evolution Strategy (CMA-ES) تفاصيل المقالة -
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7 - Workflow Scheduling on Hybrid Fog-Cloud Environment Based on a Novel Critical Path Extraction Algorithm
Fatemeh Davami Sahar Adabi Ali Rezaee Amir Masoud RahamniIn the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has أکثرIn the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has been proposed to be the main challenge in Cloud and or Fog computing environments. For resolving this issue, the present study offers a scheduling algorithm according to the critical path extraction, referred to as the Critical Path Extraction Algorithm (CPEA). In fact, it is one of the new multi-criteria decision-making algorithms to extract the critical paths of multiple workflows because it is of high importance to find the critical path in the creation and control of the scheduling. Moreover, an extensive software simulation investigation has been performed to compare this new algorithm in the real work-loads and recent algorithm. We compare our algorithm with the GRP-HEFT algorithm. The experimental results confirm the proposed algorithm's superiority in fulfilling make-span and waiting time and that workflow scheduling based on CPEA further improves the workflow make-span and waiting time. تفاصيل المقالة -
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8 - An Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Hanieh Ghorashi Meghdad MirabiCloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduli أکثرCloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distributed system in order to optimize resource utilization and response time. In this paper, an optimization-based method for task scheduling is presented in order to improve the efficiency of cloud computing. In the proposed approach, three criteria for scheduling, including the task execution time, the task transfer time, and the cost of task execution have been considered. Our method not only reduces the execution time of the overall tasks but also minimizes the maximum time required for task execution. We employ the Multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) for solving the scheduling problem. To evaluate the efficiency of the proposed method, a real cloud environment is simulated, and a similar method based on Multi-Objective Particle Swarm Optimization is applied. Experimental results show the superiority of our approach over the baseline technique. تفاصيل المقالة -
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9 - HHC-PSS: حل مسئله خدمات مراقبتی- درمانی در منزل با رویکرد زمانبندی پروژه با منابع محدود
حمیدرضا یوسف زادهدر مسئله خدمات مراقبتی-درمانی در منزل (HHC)، تخصیص تیم‌های پزشکی به بیماران و زمانبندی اعضای آنها به صورت دستی انجام می­گیرد که چنین رویکردی یک فرآیند زمان‌بر بوده و گاهاً با تخصیص بهینه فاصله دارد. در این مقاله برآنیم تا با رویکردی ابتکاری جدید مبتنی بر زمانبندی أکثردر مسئله خدمات مراقبتی-درمانی در منزل (HHC)، تخصیص تیم‌های پزشکی به بیماران و زمانبندی اعضای آنها به صورت دستی انجام می­گیرد که چنین رویکردی یک فرآیند زمان‌بر بوده و گاهاً با تخصیص بهینه فاصله دارد. در این مقاله برآنیم تا با رویکردی ابتکاری جدید مبتنی بر زمانبندی پروژه با منابع محدود، به بررسی مسئله تخصیص زمانبندی جهت زمانبندی تیم‌های پزشکی به بیماران بپردازیم. از جمله مزیت‌های چنین رویکردی میتوان به استفاده از قضایا، مسائل نمونه‌ای استاندارد و شیوه‌های (فرا)ابتکاری متنوع زمانبندی جهت بهبود کیفیت تخصیص و همچنین تعیین حداقلی تعداد نیروهای انسانی مورد نیاز برای پوشش دادن تمام خدمات پزشکی درخواست شده توسط بیماران اشاره کرد. در این رویکرد با تعریف یک قاعده اولویت پویا و استفاده از شیوه زمانبندی موازی در قالب یک الگوریتم پیشنهادی به حل مسئله HHC می‌پردازیم. از جمله معیارهای ارزیابی برای بررسی کیفیت جوابهای شدنی حاصل از زمانبندی میتوان به کمینه کردن مدت زمان سفر اعضای تیم‌های پزشکی، کاهش ساعات اضافه‌کاری، استفاده حداکثری از پتانسیل نیروهای انسانی و غیره اشاره کرد. مجموعه جوابهای شدنی مسئله در محدودیت‌هایی مانند مدت زمان کاری قید شده در قرارداد، پنجره زمانی سخت هر خدمت، استراحت اجباری و تخصیص مطلوب تیم پزشکی به بیماران (متناسب با نوع خدمت خواسته شده توسط بیمار) صدق می‌کنند. نتایج عددی حاصل از اعمال الگوریتم پیشنهادی بر روی مسائل کتابخانه‌ای کولیش، به منظور تجزیه و تحلیل رویکرد جدید ابتکاری آورده شده است که نشان از توانایی بالای این نوع رویکرد تبدیلی جدید در حل مسئله HHC دارد. تفاصيل المقالة -
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10 - برنامهریزی منابع برای مسئله انتخاب و زمانبندی سبد پروژه خودتامین مالی در سازمانهای پروژه محور
سید مهدی میرخورسندی لنگرودی حسین خسروی علیرضا داودی مجتبی موحدی فرسازمانهای پروژه محور یکی از شکل‌های سازمانی نوظهور میباشد که حول پروژه‌ها و تیم‌ها شکل می‌گیرند. این سازمانها دارای مرزها و زمینه‌های کاری پویا هستند و در آنها تعداد و اندازه پروژه‌های سازمان به طور مرتب تغییر می‌یابند. مدیران این سازمانها همواره با مسئله انتخاب اقتص أکثرسازمانهای پروژه محور یکی از شکل‌های سازمانی نوظهور میباشد که حول پروژه‌ها و تیم‌ها شکل می‌گیرند. این سازمانها دارای مرزها و زمینه‌های کاری پویا هستند و در آنها تعداد و اندازه پروژه‌های سازمان به طور مرتب تغییر می‌یابند. مدیران این سازمانها همواره با مسئله انتخاب اقتصادی‌ترین پروژه‌ها برای سازمان‌هایشان و همچنین مدیریت منابع برای پروژه‌های انتخاب شده مواجه می‌باشند. در این پژوهش مدل ریاضی مدیریت منابع تجدیدپذیر و تجدیدناپذیر برای سازمانهای پروژه محور خود تامین مالی ارائه شده است. بدین معنی که، تامین مالی سازمان صرفا از محل سرمایه اولیه سازمان و نیز درآمد پروژه‌های تکمیل شده میباشد. مدلسازی ریاضی مدیریت منابع در مسئله انتخاب و زمانبندی سبد پروژه خودتامین مالی در یک سازمانهای پروژه محور برای اولین بار در مقاله حاضر ارائه شده است. در این خصوص، با استفاده از تئوری سبد پروژه، انتخاب و زمانبندی پروژه‌ها درون یک سازمان پروژه محور با توجه به محدودیت منابع تجدیدپذیر و تجدیدناپذیر، وجود رابطه پیش‌نیازی میان فعالیتهای پروژه‌ها، در نظرگیری ارزش زمانی سرمایه برای منابع مالی و نهایتا بکارگیری استراتژی درآمدزایی حین کار صورت گرفته است. تابع هدف بصورت دوهدفه ارزش خالص فعلی سرمایه‌گذاری را بیشینه و همچنین منابع تجدیدپذیر بیکار در حین انجام سبد را کمینه می‌نماید. مدلسازی بصورت برنامهریزی عدد صحیح مختلط بوده و پس از خطی‌سازی مدل، از روش LP متریک برای حل تابع هدف چند هدفه استفاده شده است و نهایتا نتایج بر روی مثال عددی مورد بررسی قرار گرفته است. نتایج نشان‌دهنده مدیریت بهینه منابع در مسئله انتخاب و زمانبندی سبد پروژه خود تامین مالی میباشد. تفاصيل المقالة -
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11 - ارائه یک مدل بهینه سازی چندهدفه جهت زمانبندی و مسیریابی پرستاران در ارائه خدمات پزشکی در منزل
حمیدرضا یوسف زاده سمیه هراتی مطلق موسی الرضا شمسیه زاهدیامروزه با رشد روزافزون جمعیت و همچنین عواملی مانند افزایش افراد سالمند، افزایش تعداد بیمارانی که ازبیماریهای مزمن رنج می برند، تقاضا برای دریافت مراقبتهای پزشکی در منزل (HHC) در حال افزایش است. مراکز ارائه دهنده خدمات مراقبتی پزشکی همواره به دنبال راهکارهایی جهت برنامه أکثرامروزه با رشد روزافزون جمعیت و همچنین عواملی مانند افزایش افراد سالمند، افزایش تعداد بیمارانی که ازبیماریهای مزمن رنج می برند، تقاضا برای دریافت مراقبتهای پزشکی در منزل (HHC) در حال افزایش است. مراکز ارائه دهنده خدمات مراقبتی پزشکی همواره به دنبال راهکارهایی جهت برنامه ریزی و زمانبندی دقیق ارائه خدمات مراقبتی - درمانی هستند تا علاوه برکمینه کردن هزینه های خود، میزان رضایت بیماران و پرستاران را بیشینه نمایند. در این راستا، ازیک سو بیمار تمایل دارد تا با در نظر گرفتن مهارت پرستار اختصاص داده شده، در پنجره زمانی مورد ترجیحش ملاقات شود. از سوی دیگر، پرستار نیز ترجیح می دهد که در پنجره زمانی مورد مطلوب خود به ارائه خدمات بپردازد. علاوه بر این موارد، حفظ قوانین ساعت کاری در قرارداد، رعایت بازه های زمانی نرم و سخت ارائه خدمات و استراحت های الزامی از محدودیت هایی هستند که ضروری است در این نوع مسائل در نظر گرفته شوند. اهداف این مقاله کمینه کردن زمان رفت و آمد پرستاران و بیشینه نمودن همزمان سطح رضایت بیماران و پرستاران و همچنین کاهش ساعات اضافه کاری پرستاران می باشد که با در نظر گرفتن ترجیحات پرستاران و بیماران و اختصاص استراحت های اجباری به پرستاران بعد از مدت زمان کاری مشخص،در قالب یک مدل برنامه ریزی ریاضی چندهدفه ارائه می گردد. در ادامه به منظوربررسی و تحلیل عملکرد مدل پیشنهادی، با در نظر گرفتن معیار توقف بر روی زمان حل مسئله، مدل پیشنهادی را بر روی مجموعه ای از مسائل تصادفی متفاوت مورد آزمون قرار می دهیم. تفاصيل المقالة -
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12 - ارائه مدل ریاضی چندهدفه برای مسأله تبادل هزینه -زمان و در نظر گرفتن ارزش زمانی پول با استفاده از الگوریتم MOPSO
محمدعلی شفیعی محمدرضا شهریاری فرهاد حسین‌زاده‌لطفی رضا رادفرمسأله تبادل هزینه و زمان یکی از مهمترین مسائل موجود در زمینه زمانبندی پروژه میباشد و تاکنون تحقیقات بسیار زیادی با رویکردهای گوناگون کمی‌و کیفی بر روی این موضوع انجام شده است. در این تحقیق قصد داریم تا با ارائه یک مدل دو هدفه ریاضی، شرایط را برای ایجاد توازن میان فشر أکثرمسأله تبادل هزینه و زمان یکی از مهمترین مسائل موجود در زمینه زمانبندی پروژه میباشد و تاکنون تحقیقات بسیار زیادی با رویکردهای گوناگون کمی‌و کیفی بر روی این موضوع انجام شده است. در این تحقیق قصد داریم تا با ارائه یک مدل دو هدفه ریاضی، شرایط را برای ایجاد توازن میان فشرده‌سازی، صرفه‌جویی در هزینه و به تاخیر انداختن زمان اجرای فعالیت‌ها مهیا کنیم به طوری که ابزار مناسبی در اختیار تصمیم‌گیرندگان برای تصمیم‌گیری در رابطه با زمان اجرای هر فعالیت با توجه به امکانات در دسترس و نیز زمان در اختیار، برای اتمام پروژه فراهم آید. در مدل ریاضی پیشنهادی تلاش شده است تا با به کارگیری فرضیاتی نظیر تابع هزینه غیرخطی و همچنین در نظر گرفتن ارزش زمانی پول، شرایط مسئله تا حد امکان به محیط واقعی نزدیکتر گردد. در پایان مدل ریاضی ارائه شده در این مقاله را با استفاده از الگوریتم Objective Particle Swarm Optimization)MOPSO(Multi بررسی نموده و تاثیر فشرده‌سازی و به تاخیر انداختن فعالیت‌ها را بر روی مجموعه نامغلوب نهایی ارائه خواهیم داد. تفاصيل المقالة -
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13 - بهینه‌سازی زمان‌های آماده‌سازی با در نظر داشتن زمانبندی تعمیر و نگهداری با استفاده از مدلسازی غیرخطی
آرش زارع طلب محمدرضا شهریاری سعیده نادریمقاله پیش‌رو، با عنوان "بهینه‌سازی زمان‌های آماده‌سازی با در نظر داشتن زمانبندی تعمیر و نگهداری با استفاده از مدلسازی غیرخطی" با هدف طراحی و ارائه یک مدل ریاضی سعی در بدست آوردن بهترین توالی عملیات که منجر به مینیمم‌سازی زمان‌های آماده‌سازی و در نهایت مینیمم‌سازی زمان أکثرمقاله پیش‌رو، با عنوان "بهینه‌سازی زمان‌های آماده‌سازی با در نظر داشتن زمانبندی تعمیر و نگهداری با استفاده از مدلسازی غیرخطی" با هدف طراحی و ارائه یک مدل ریاضی سعی در بدست آوردن بهترین توالی عملیات که منجر به مینیمم‌سازی زمان‌های آماده‌سازی و در نهایت مینیمم‌سازی زمان کلی تولید را در پی خواهد داشت، صورت پذیرفته است. این پژوهش ناظر بر کاهش زمان و همچنین هزینههای تولید در پی اجرای مدل ارائه شده میباشد. روش گردآوری اطلاعات و داده‌های تحقیق، بررسی و مطالعه منابع کتابخانه‌ای، مراجعه به اسناد بخش‌های تعمیر نگهداری و تولید در شرکت و مدیران صاحب‌نظر در قسمت­های برنامهریزی، تولید و مهندسی... بوده است. در ادامه مدل با در نظر گرفتن محدودیتهای مربوط به هزینه‌ها و زمان و همچنین محدودیتهای سیستم تولیدی ارائه شده است. برای حل مدل از نرم‌افزارLINGO استفاده شده و خروجی‌های مدل جوابهای local که نشان دهنده بهترین توالی خواهد بود را ارائه خواهد داد. و در نهایت میتوان با تغییرات اندکی مدل را به واحدهای صنعتی دیگر نیز تعمیم داد و بهترین توالی عملیاتی را در خصوص ماشین‌های چندکاره ارائه نمود. تفاصيل المقالة -
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14 - ارزیابی مدل AquaCrop در شبیه‌سازی عملکرد زعفران تحت سناریوهای مختلف کم‌آبیاری و مصرف زئولیت
نیازعلی ابراهیمی پاک محسن احمدی اصلان اگدرنژاد عباس خاشعی سیوکیاین پژوهش به‌منظور ارزیابی عملکرد و زیست‌توده زعفران با استفاده از مدل رشد گیاهی AquaCrop تحت گزینه‌های مختلف کم‌آبیاری و مصرف زئولیت با استفاده از نتایج آزمایش سال 1392 و 1393 انجام شد. در تحقیق انجام شده، 36 داده اندازه‌گیری شده برای هر پارامتر تحت تیمارهای سطح آبیاری أکثراین پژوهش به‌منظور ارزیابی عملکرد و زیست‌توده زعفران با استفاده از مدل رشد گیاهی AquaCrop تحت گزینه‌های مختلف کم‌آبیاری و مصرف زئولیت با استفاده از نتایج آزمایش سال 1392 و 1393 انجام شد. در تحقیق انجام شده، 36 داده اندازه‌گیری شده برای هر پارامتر تحت تیمارهای سطح آبیاری (عرف محلی: I1، کم‌آبیاری با کاهش 70 درصد نیاز آبی گیاه: I2 و آبیاری براساس نیاز آبی کامل گیاه: I3) و کاربرد زئولیت (صفر: Z0، 5/0 درصد: Z1، 1درصد: Z2 و 2 درصد: Z3 درصد وزنی خاک) به‌صورت تصادفی به دو دسته تقسیم شدند. دسته نخست (شامل70 درصد داده‌ها) به‌منظور واسنجی و دسته دوم (شامل 30 درصد داده‌ها) برای صحت‌سنجی مدل AquaCrop مورد استفاده قرار گرفتند. نتایج شبیه‌سازی نشان داد در هر دو مرحله واسنجی و صحت‌سنجی، تیمارهای شامل آبیاری عرف محلی بیشترین اختلاف را با مقادیر اندازه‌گیری شده داشتند. در برخی موارد تیمارهای حاوی زئولیت این اختلاف را کاهش دادند لیکن رابطه معنی‌داری بین نتایج به‌دست آمده مشاهده نشد. آماره‌های RMSE، MBE و NRMSE برای شبیه‌سازی عملکرد زعفران در مرحله صحت‌سنجی به ترتیب برابر با 48/0 (کیلوگرم در هکتار)، 21/0- (کیلوگرم در هکتار) و 09/0 و برای زیست‌توده در همین مرحله به ترتیب برابر با 9/151 (کیلوگرم در هکتار)، 2/74 (کیلوگرم در هکتار) و 13/0 به دست آمدند. این مقادیر نشان دادند که این مدل دقت مناسبی برای شبیه‌سازی عملکرد و زیست توده زعفران داشت. کارایی این مدل با استفاده از مقادیر EF مطلوب بود به طوری که مقدار این آماره برای عملکرد در هر دو مرحله واسنجی و صحت‌سنجی به ترتیب برابر با 32/0 و 42/0 و برای زیست‌توده در همین دو مرحله به ترتیب برابر با 99/0 و 99/0 بود. براساس نتایج به دست آمده،این مدل دقت کافی برای شبیه‌سازی عملکرد و زیست‌توده زعفران در شرایط کم آبیاری و کاربرد زئولیت را داشت. بنابراین استفاده از این مدل، به‌عنوان یک مدل مطلوب گیاهی برای شبیه سازی زعفران پیشنهاد میشود. تفاصيل المقالة -
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15 - شبیه‌سازی برنامهریزی آبیاری گیاه سویا با استفاده از مدل BUDGET
مهدی سرائی تبریزیپیش بینی و برنامه ریزی دقیق آبیاری گیاهان می تواند ضمن جلوگیری از تنش های احتمالی دوره ای، کارایی مصرف آب را نیز افزایش دهد. در این پژوهش، عملکرد مدل BUDGET در برنامه ریزی آبیاری در مقابل داده های تحت مدیریت کم آبیاری سویا برای دو سال زراعی متوالی 88-1387 و 89-1388 مورد أکثرپیش بینی و برنامه ریزی دقیق آبیاری گیاهان می تواند ضمن جلوگیری از تنش های احتمالی دوره ای، کارایی مصرف آب را نیز افزایش دهد. در این پژوهش، عملکرد مدل BUDGET در برنامه ریزی آبیاری در مقابل داده های تحت مدیریت کم آبیاری سویا برای دو سال زراعی متوالی 88-1387 و 89-1388 مورد ارزیابی قرار گرفت. این پژوهش در قالب طرح بلوک های کامل تصادفی در چهار تیمار آبیاری سطحی شیاری شامل تیمار آبیاری کامل (تیمار شاهد)، تیمار کم آبیاری سنتی درحد 75 و 50 درصد جبران نقصان رطوبتی خاک و تیمار آبیاری بخشی منطقه ریشه درحد 50 درصد جبران نقصان رطوبتی خاک انجام شد. هر تیمار دارای سه تکرار بود. نتایج نشان داد که شاخص های ارزیابی مدل RMSE و CRM در سال 1387 به ترتیب برابر 91/3 و 18/0- و در سال 1388 به ترتیب 76/4 و 11/0- بود. شاخص EF در سال زراعی 87 و 88 به ترتیب برابر 69/0 و 78/0 به دست آمد که نشان دهنده کارایی قابل قبول مدل در پیش بینی عملکرد می باشد. نتایج این تحقیق نشان می دهد که کاربرد مدل BUDGET با اصلاح ضرایب گیاهی در مراحل مختلف رشد گیاه و ویژگی های خاک و گیاه می تواند نتایج دقیق تری ارائه کند. همچنین، نتایج حاصل از تحلیل حساسیت مدل نشان داد که مدل BUDGET نسبت به عمق آب آبیاری و رطوبت اولیه خاک در تیمار آبیاری کامل حساسیت کمی دارد. تفاصيل المقالة -
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16 - Due Date Assignment and JIT Scheduling Problem in Blocking Hybrid Flow Shop Robotic Cells with Multiple Robots and Batch Delivery Cost
J. Rezaeian N. Derakhshan I. Mahdavi R. Alizadeh ForoutanIn this paper, just-in-time scheduling problem with batch delivery and due date assignment for hybrid flow shop robotic cells is considered. A mixed integer linear programming (MILP) model is presented to determine the sequence of jobs and robot moves. Two meta-heuristi أکثرIn this paper, just-in-time scheduling problem with batch delivery and due date assignment for hybrid flow shop robotic cells is considered. A mixed integer linear programming (MILP) model is presented to determine the sequence of jobs and robot moves. Two meta-heuristic algorithms including Artificial Immune System (AIS) and Tabu Search (TS) are proposed. The results show that AIS performs well for this problem. تفاصيل المقالة -
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17 - A multi-product vehicle routing scheduling model with time window constraints for cross docking system under uncertainty: A fuzzy possibilistic-stochastic programming
B. Vahdani SH. Sadigh BehzadiMathematical modeling of supply chain operations has proven to be one of the most complex tasks in the field of operations management and operations research. Despite the abundance of several modeling proposals in the literature; for vast majority of them, no effective أکثرMathematical modeling of supply chain operations has proven to be one of the most complex tasks in the field of operations management and operations research. Despite the abundance of several modeling proposals in the literature; for vast majority of them, no effective universal application is conceived. This issue renders the proposed mathematical models inapplicable due largely to the fact that real-life supply chain problems are set forth in restrained terms or represented less strikingly than they would bear out. This paper is triggered to bridge this gap by proposing a universal mixed integer linear programming (MILP) framework which to large extent simulates many realistic considerations in vehicle routing scheduling problems in cross-docking systems which might have separately been attempted by other researchers. The developed model is pioneer in excogitating the vehicle routing scheduling problem with the following assumptions: a) multiple products are transported between pick-up and delivery nodes, b) delivery time-intervals are imposed on each delivery node, c) multiple types of vehicles operate in the system, d) capacity constraints exists for each vehicle type, and finally e) vehicles arrives simultaneously at cross-docking location. Moreover, to solve the model a hybrid solution methodology is presented by combining fuzzy possibilistic programming and stochastic programming. Finally, in order to demonstrate the accuracy and efficiency of the proposed model, an extensive sensitivity analysis is performed to scrutinize its parameters’ demeanors. تفاصيل المقالة -
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18 - مشارکت واحدها با در نظر گرفتن احتمالی ذخیره چرخان و بار قطع پذیر
امیر حسین باباعلی محمدتقی عاملیدر این مقالهروی بحث های احتمالی در UC کار شده است، به طوریکه رزرو چرخان و بار قطع پذیر به عنوان رزرو بهره برداری به حساب می آیند. انرژی تأمبن نشده مورد انتظار (EENS) به عنوان ملاکی برای احتمال لحاظ شده است و روشی جدید جهت محاسبه این شاخص در حضور بار قطع پذیر پیشنهاد شده أکثردر این مقالهروی بحث های احتمالی در UC کار شده است، به طوریکه رزرو چرخان و بار قطع پذیر به عنوان رزرو بهره برداری به حساب می آیند. انرژی تأمبن نشده مورد انتظار (EENS) به عنوان ملاکی برای احتمال لحاظ شده است و روشی جدید جهت محاسبه این شاخص در حضور بار قطع پذیر پیشنهاد شده است. قید قابلیت اطمینان مسأله 1Unit Commitment،(RCUC) بر اساس برنامه ریزی ترکیب خطی (MIP) به شکل ریاضی بیان شده است. مهمترین محدودیت اقتصادی هزینه انرژی می باشد. و از لحاظ فنی با درنظر گرفتن بارهای قطع پذیر و رزرو چرخان به کمک مباحث احتمالی میتوان مقدار انرژی تأمین نشده را کاهش داد و بالطبع قابلیت اطمینان مشارکت واحدها را بالا برد. تفاصيل المقالة -
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19 - Optimization of scheduling information in a network-based Standard IEEE802. 17 and measurement for video transmission
Ehsan Korbekandi Mohsen Ashourian Sayed Ali HashemiOne of looped networks that in recent years has been much noticed is standard known as IEEE 802.17 RPR ring network or the return packet. Architecture RPR ring network protocol that transmits data between nodes connected in a double ring structure to support. RPR has tw أکثرOne of looped networks that in recent years has been much noticed is standard known as IEEE 802.17 RPR ring network or the return packet. Architecture RPR ring network protocol that transmits data between nodes connected in a double ring structure to support. RPR has two single transit buffer structure (STB) and double transit buffer (DTB), respectively. Single transit buffer architecture, just a high-priority traffic buffering (HP) and low priority (LP) passing through the ring buffer architecture serves and double, two separate buffer for high-priority and low priority traffic is considered passing.Send information for scheduling algorithms used in network nodes RPR, queue priority (Priority-Queue), respectively. In this way, the separation of traffic based on priority and high priority traffic has absolute priority over lower priority traffic so that always the highest priority to transit buffer appropriated therefore of high priority traffic such as video packet, the nodes access to congested suffered numerous delays and instability vibration are ring (Jitter).In this thesis addition to scheduling priority queue, plans, schedules DRR and DRR + to increase the quality of service to traffic with high priority on congested node in a network with a ring structure with 10 nodes software Opnet simulation and the performance timing of passing information about at least two network nodes in the hub scenario (hUB) in which all the nodes transmit information to a node with video traffic conditions, congestion were examined happened and qualitative results were compared to that, the display shows the relative improvements in reducing delays and instability shaking changes in the timing of DRR and DRR + compared to the recommended standard. تفاصيل المقالة -
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20 - A Review of Scheduling and Resource Allocation Algorithms with a Load Balancing Approach in Cloud Computing
Yaser RamzanpoorCloud computing is a distributed environment for providing services over the Internet. Load balancing of computing resources has emerged as a crucial element in this industry as a result of the expanding use of cloud computing and the expectations of customers to receiv أکثرCloud computing is a distributed environment for providing services over the Internet. Load balancing of computing resources has emerged as a crucial element in this industry as a result of the expanding use of cloud computing and the expectations of customers to receive more services and better outcomes. The workload and system behavior of cloud computing are quite dynamic. And this can cause the resources in the data center to be overloaded. Ultimately, a load imbalance in some data center resources could result in increased energy use, decreased performance, and resource waste. Response time, expense, throughput, performance, and resource usage are among the quality of service indicators that load balancing can enhance. In this article, we analyze and evaluate scheduling and resource allocation methods with a view to load balancing, review the most recent approaches, and give a classification of these algorithms. Also, several significant problems and difficulties with cloud load balancing will be discussed in an upcoming study to create new algorithms. تفاصيل المقالة -
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21 - برنامهریزی بهینه یکپارچه توان اکتیو و راکتیو در ریزشبکه های هوشمند با امکان وقوع یک ساعت کارکرد جزیره‌ای
پرستو خادمی آستانه حسین شیخ شاهرخ دهکردیدر شبکه های هوشمند برق، تجهیزات و زیرساخت های الکتریکی هوشمند به منظور افزایش بازده، بهبود قابلیت اطمینان و کاهش آلودگی های زیست محیطی با هم ادغام می گردند. در سال های اخیر مفهوم ریزشبکه به معنای یک شبکه توزیع ولتاژ متوسط یا ولتاژ پایین شامل واحدهای تولید پراکنده، ذخیره أکثردر شبکه های هوشمند برق، تجهیزات و زیرساخت های الکتریکی هوشمند به منظور افزایش بازده، بهبود قابلیت اطمینان و کاهش آلودگی های زیست محیطی با هم ادغام می گردند. در سال های اخیر مفهوم ریزشبکه به معنای یک شبکه توزیع ولتاژ متوسط یا ولتاژ پایین شامل واحدهای تولید پراکنده، ذخیره سازها و بارهای کنترل شونده مختلف با قابلیت بهره برداری در هر دو حالت متصل به شبکه و جزیره ای پیشنهاد گردیده است. چون ریزشبکه در حالت جزیره ای، شبکه ای با واحدهای تولید توان کوچک است، کوچکترین اغتشاشی ممکن است موجب ناپایداری آن شود. لذا ضرورت دارد تا در هنگام گذر از حالت متصل به شبکه به حالت جزیره ای از وجود ذخیره کافی در ژنراتورهای تولید پراکنده با توجه به منحنی قابلیت تولید آن ها به منظور تامین توان اکتیو و راکتیو بارهای مصرفی اطمینان حاصل شود. تمرکز اصلی این مقاله بر روی برنامه ریزی بهینه یکپارچه توان اکتیو و راکتیو در ریزشبکه های هوشمند با امکان وقوع 1 ساعت کارکرد جزیره ای می باشد. ضرورت گذر پایدار از حالت متصل به شبکه به حالت جزیره ای در صورت وقوع خطا در شبکه از قیود بسیار مهم در ریزشبکه ها می باشد. بنابراین برنامه ریزی اقتصادی واحدهای تولید پراکنده یک ریزشبکه با در نظر گرفتن این قیود مورد بررسی قرار می گیرد. نتایج نشان می دهند در صورت در نظر گرفتن قید امنیت گذر پایدار ریزشبکه، هزینه بهره برداری از آن افزایش یافته ولی قابلیت اطمینان آن نیز بیشتر می گردد. هزینه های بهره برداری در مطالعات موردی محاسبه شده است. با شدیدتر شدن تعداد باز ه های زمانی که ریزشبکه باید در حالت جزیره ای مورد بهره برداری قرار بگیرد، هزینه بهره برداری نیز افزایش می یابد. همچنین با در نظر گرفتن نایقینی های موجود در مسئله، مدل دقیق تر شده ولی هزینه بهره برداری نیز افزایش می یابد. تفاصيل المقالة -
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22 - یک مدل زمانبندی وظایف در منابع ناهمگن ابری با ترکیبی از الگوریتم های هوش جمعی
صفدر رستمی علی برومندنیا احمد خادم زادهرایانش ابری محیطی ست ،که کاربران براساس تقاضا و پرداخت به ازای استفاده به منابع محاسباتی اشتراکی دسترسی دارند. با توجه به محدودیت و پویایی منابع محاسباتی برای اجرای درخواست‌های متنوع و متغیر با زمان کاربران، نیاز به یک مکانیزم زمانبندی موثر برای رسیدگی به شرایط پویا أکثررایانش ابری محیطی ست ،که کاربران براساس تقاضا و پرداخت به ازای استفاده به منابع محاسباتی اشتراکی دسترسی دارند. با توجه به محدودیت و پویایی منابع محاسباتی برای اجرای درخواست‌های متنوع و متغیر با زمان کاربران، نیاز به یک مکانیزم زمانبندی موثر برای رسیدگی به شرایط پویای سیستم و بهره وری منابع و رضایت کاربران امری حیاتی می باشد. از آنجایی که تخصیص وظایف به منابع یک چالش اساسی در محیط های ابری به شمار میرود الگوریتم‌های بسیاری جهت کاهش زمان اجرا و موازی‌سازی زیروظایف ارائه شده است. الگوریتم‌های زمانبندی موجود تلاش می‌کنند با توجه به وضعیت فعلی سیستم، یک زمانبندی بهینه بین منابع و وظایف با توجه به پویایی درخواست های کاربران فراهم آورند، ولی با این وجود اغلب این روش ها نتوانسته اند در بلندمدت نتیجه مطلوبی را ارائه دهند. به دلیل سرعت همگرایی پایین راه‌حل‌ها در الگوریتم‌های فرااکتشافی در این مقاله یک روش زمانبندی متناسب با صفهای اولویت چندگانه مبتنی بر رتبه‌بندی نامغلوب و به کمک الگوریتم بهینه سازی جستجوی کاپوچین برای سیستمهای ابری ناهمگن ارائه شده است. نتایج شبیه سازی نشان میدهد که روش پیشنهادی در مقایسه با روش های پیشین از نظر تاخیر، توازن بار و زمان اجرا بهتر عمل می‌کند. تفاصيل المقالة -
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23 - Dynamic Programming for Multi-Crew Scheduling of the Emergency Repair of Network
Mehrdad Niyazi Javad BehnamianOne of the most necessary operations in humanitarian logistics is the distribution of relief goods to the population in disaster areas. When a disaster occurs, some parts of the distribution infrastructure may be damaged and consequently make it impossible to reach all أکثرOne of the most necessary operations in humanitarian logistics is the distribution of relief goods to the population in disaster areas. When a disaster occurs, some parts of the distribution infrastructure may be damaged and consequently make it impossible to reach all the demand nodes and delivering the relief goods. In this study, we focus on the planning of infrastructure recovery efforts in post-disaster response. The problem is the scheduling of the emergency repair of a network that has been damaged by a disaster. The objective is to maximize network accessibility for all demand nodes in order to deliver relief goods to them. We adopt a dynamic programming algorithm to solve the problem when more than one crew group is available. Our numerical analysis of the solution shows the performance of the algorithm. We, also, compare our results with some similar studies to indicate the differences between one and multi-crew scheduling. تفاصيل المقالة -
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24 - A Goal Programming Linear Model for Simultaneous Project Scheduling and Resource Leveling - a Huge Civil Project as a Case Study
Yousef RabbaniWe have a huge civic project, includes several sub-projects, which are divided into activities. This project is a project to rehabilitate 550,000 hectares of agricultural land in the provinces of Khuzestan and Ilam. The project has been divided according to the plots of أکثرWe have a huge civic project, includes several sub-projects, which are divided into activities. This project is a project to rehabilitate 550,000 hectares of agricultural land in the provinces of Khuzestan and Ilam. The project has been divided according to the plots of land. The Jehad in Tehran is managing the projects. They need project scheduling as well as resource levelling and "lot-sizing". Levelling and lot sizing are the most important issues in utilizing the limited resources. For determining the scope and the size of those sub-projects as well as their parallel activities, so far, many models have been proposed. However, the models are weak either in higher resource utilization or in solving numerically the problems. In this paper, our effort has been concentrated on developing scheduling, resource levelling, and lot sizing model, based on balancing utilization of resources, so that the real size civil project could be solved within an acceptable duration time. This paper proposes a goal programming linear model for simultaneous project scheduling and resource levelling. This model determines the best schedule of sub-activities (optimal "lot size" of each sub-activity) to reach the minimum amount of diversion of resources consumed from the number of resources available for the entire periods of the planning horizon. In fact, if the best "lot sizes" have been taken, then minimum fluctuation of the active resources is reached. The proposed model has been used to schedule a project with 87 activities. This project has been scheduled and, accordingly, the optimal volume (the "lot size") of sub-activities have been determined for each activity at any period of time. In this way, only 4 resources out of a total of 32 resources are in shortage. In contrast, the scheduling of this project, using the CPM, results in a shortage of 13 resources. تفاصيل المقالة -
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25 - Parallel Machine Scheduling with Controllable Processing Time Considering Energy Cost and Machine Failure Prediction
Yousef Rabbani Ali Qorbani Reza Kamran RadPredicting unexpected incidents and energy consumption decline is one of the current problems in the industry. The extant study addressed parallel machine scheduling by consideration of failures and energy consumption decline. Moreover, the present paper aimed at minimi أکثرPredicting unexpected incidents and energy consumption decline is one of the current problems in the industry. The extant study addressed parallel machine scheduling by consideration of failures and energy consumption decline. Moreover, the present paper aimed at minimizing early and late delivery penalties, and enhancing tasks. This research designed a mathematical model for this problem that considered processing times, delivery time, rotation speed and torque, failure time, and machine availability after repair and maintenance. Failure times have been predicated on using machine learning algorithms. The results indicated that the proposed model can be suitably solved for the size of 10 jobs or tasks and five machines. This research addresses the problem in two parts: the first part predicts failures, and the second part includes the sequence of parallel machine scheduling operations. After the previous data were received in the first step, machine failure was predicted by using machine learning algorithms, and a set of rules were obtained to correct the process. The obtained rules were used in the model to improve the machining process. In the second step, scheduling mode was used to determine operations sequence by consideration of these failures and machinery unavailability to achieve the optimal sequence. Moreover, it is supposed to reduce energy consumption and failures. This study used the Light GBM algorithm and achieved 85% precision in failure prediction. The rules obtained from this algorithm contributed to cost reduction. تفاصيل المقالة -
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26 - A Heuristic Algorithm for Solving Single Machine Scheduling Problem with Periodic Maintenance
Amir Ebrahimi Zade Mohammad Bagher Fakhrzad Mohsen HasaninezhadAbstract. In this paper, the scheduling problem with nonresumable jobs and maintenance process is considered in order to minimize the makespan under two alternative strategies. The first strategy is to implement the maintenance process on the machine after a predetermin أکثرAbstract. In this paper, the scheduling problem with nonresumable jobs and maintenance process is considered in order to minimize the makespan under two alternative strategies. The first strategy is to implement the maintenance process on the machine after a predetermined time period and the second one is to consider the maximum number of jobs that can be done with an especial tool. We propose a new mathematical formulation for the aforementioned problem and regarding the problem is included in the NP-Hard class of problems, in the second part of the paper, we propose a heuristic algorithm in order to solve the problem in a reasonable time. Also we compare the performance of the proposed algorithm with existing methods in the literature. Computational results showed that the proposed algorithm is able to attain optimum solutions in most cases and also corroborate its better performance than the existing heuristic methods in the literature. تفاصيل المقالة -
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27 - A Genetic Algorithm with Modified Crossover Operator for a Two-Agent Scheduling Problem
Maziyar Yazdani Fariborz JolaiThe problem of scheduling with multi agent has been studiedfor more than one decade and significant advances have been madeover the years. However, most work has paid more attention to the conditionthat machines are available during planning horizon. Motivatedby the obs أکثرThe problem of scheduling with multi agent has been studiedfor more than one decade and significant advances have been madeover the years. However, most work has paid more attention to the conditionthat machines are available during planning horizon. Motivatedby the observations, this paper studies a two-agent scheduling modelwith multiple availability constraint. Each agent aims at minimizing afunction which depends only on the completion times of its jobs. Theproblem is to find a schedule that minimizes the objective function ofone agent, subject to the objective function of the other agent does notexceed a given threshold Q. some new dominance properties for thisproblem percent and next, using these properties, we develop a geneticalgorithm with modified crossover for the problem. Computational resultsare also presented to determine the performance of the proposedgenetic algorithms. تفاصيل المقالة -
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28 - Staff Scheduling by a Genetic Algorithm
Ahmad Reza Tahanian Maryam KhaleghiThis paper describes a Genetic Algorithms approach to amanpower-scheduling problem arising at a Petrochemical Company. AlthoughGenetic Algorithms have been successfully used for similar problemsin the past, they always had to overcome the limitations of theclassical Gen أکثرThis paper describes a Genetic Algorithms approach to amanpower-scheduling problem arising at a Petrochemical Company. AlthoughGenetic Algorithms have been successfully used for similar problemsin the past, they always had to overcome the limitations of theclassical Genetic Algorithms paradigm in handling the conflict betweenobjectives and constraints. The approach taken here is to use an indirectcoding based on permutations of the personnel’s, and a heuristicdecoder that builds schedules from these permutations. Computationalexperiments based on 52 weeks of live data are used to evaluate three differentdecoders with varying levels of intelligence, and four well-knowncrossover operators. The results reveal that the proposed algorithm isable to find high quality solutions and is both faster and more flexiblethan a recently published Taboo Search approach تفاصيل المقالة -
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29 - برنامهریزی همزمان نگهداری و تعمیرات و کنترل موجودی انبار قطعات یدکی: مطالعه موردی ربات شاتل پیش رنگ شرکت خودروسازی
seyd mohamad reza aboalaghaey Davood Mohammaditabar Sadigh Raissiبرنامه ریزی نگهداری و تعمیر (نت) ماشین‌آلات کارخانه یکی از ابزار مهم در کاهش هزینههای عملیاتی است؛ مدیریت کنترل موجودی قطعات یدکی نقش پررنگی در عملکرد سیاست های نت دارد. در این تحقیق مدلسازی یکپارچه موجودی قطعات یدکی و برنامهریزی نت جهت تعیین سطح بیشینه موجودی و دوره أکثربرنامه ریزی نگهداری و تعمیر (نت) ماشین‌آلات کارخانه یکی از ابزار مهم در کاهش هزینههای عملیاتی است؛ مدیریت کنترل موجودی قطعات یدکی نقش پررنگی در عملکرد سیاست های نت دارد. در این تحقیق مدلسازی یکپارچه موجودی قطعات یدکی و برنامهریزی نت جهت تعیین سطح بیشینه موجودی و دوره بازپرسازی در سیستم (S,T) به همراه تعیین زمان بهینه تعویض پیشگیرانه ارائه می شود. مجموع هزینههای مرتبط با نظام نت، نظیر هزینه سفارش دوره ای و اضطراری و هزینههای امور بازرسی و تعمیرات در تابع هدف مدل کمینه می شوند. برای نشان دادن توانمندی و کارایی مدل، نتایج مطالعه موردی در خطوط پیش رنگ یک شرکت خودروسازی برای تعیین سیاست‌های مدیریت موجودی قطعه ای پرمصرف و بحرانی پیاده‌سازی شده‌است. همچنین به‌منظور تحلیل پایداری نتایج تحقیق، حساسیت نتایج به تغییرات پارامترهای ورودی بررسی شده‌است. براساس نتایج، هزینه کل متاثر از نرخ خرابی، مدت‌زمان تأمین قطعه و هزینه تعویض قطعات معیوب است و در این خصوص بیشترین حساسیت را به مقادیر نرخ خرابی و مدت‌زمان تأمین قطعه دارد. استفاده از نتایج تحقیق در مواردی که نرخ خرابی نسبتا ثابت است توصیه میشود. تفاصيل المقالة -
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30 - طراحی یک مدل تولید کارگاهی سبز، با ایجاد توازن بین زمان تکمیل و مصرف انرژی (بررسی موردی: شرکت پدیده ماشین سازی غرب)
Maryam Rahimi alloghareh sayyed mohammad reza davoodiهدف تحقیق حاضر زمانبندی سبز در تولید کارگاهی دو ماشینه با موازنه نمودن زمان تکمیل و مصرف انرژی میباشد. روش تحقیق از نوع توصیفی _تحلیلی و بر حسب هدف کاربردی است. این تحقیق به بررسی عملکرد مسئله زمانبندی فلوشاپ چند ماشین با در نظر گرفتن توابع هدف کمینه‌سازی زمان ات أکثرهدف تحقیق حاضر زمانبندی سبز در تولید کارگاهی دو ماشینه با موازنه نمودن زمان تکمیل و مصرف انرژی میباشد. روش تحقیق از نوع توصیفی _تحلیلی و بر حسب هدف کاربردی است. این تحقیق به بررسی عملکرد مسئله زمانبندی فلوشاپ چند ماشین با در نظر گرفتن توابع هدف کمینه‌سازی زمان اتمام کل، مصرف انرژی و مجموع وزنی دیرکرد و زودکرد کارها پرداخته است. داده‌های مورد نیاز از طریق مصاحبه و اطلاعات موجود در شرکت پدیده ماشین‌سازی غرب گردآوری و سپس در نرم‌افزار متلب پیاده‌سازی شدند. تعداد 30 مسئله با ابعاد مختلف و براساس شیوه‌های رایج تولید و با الگوریتم فراابتکاری چندهدفه (NSGA-II) و الگوریتم تکاملی چندهدفه‌ی بهینه‌سازی ازدحام ذرات (MOPSO) مورد ارزیابی قرار گرفت. از سه معیار مقایسه MID، MS و SNS در کنار معیار زمان حل برای مقایسات حالات مختلف الگوریتم‌ها بهره‌گرفته شد. در نظر گرفتن ملاحظات پایداری در مسئله زمانبندی تولید و ساخت با کمینه کردن مصرف انرژی به عنوان یک معیار در برنامهریزی کارگاهی در این پژوهش مورد توجه قرار گرفته است. این امر علاوه بر مزایای اقتصادی با کاهش انتشار کربن، به محیط زیست کمک شایانی می‌نماید. نتایج حاصل از مقایسه دو الگوریتم با استفاده از دو روش تحلیل سلسله مراتبی و تاپسیس نشان داد خروجی حاصل از مقایسه الگوریتم NSGA-II نسبت به الگوریتم MOPSO، برای این مسائل عملکرد بهتری دارد. تفاصيل المقالة -
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31 - الگوریتم پرندگان فاخته توسعه یافته جهت حل یک مدل جدید زمان بندی ماشین و وسیله حمل
Hojat Nabovatiدر این مقاله یک مدل جدید زمان بندی ماشین با در نظر گرفتن امکان پذیری حمل، وابستگی زمان حمل به نوع کار، در نظر گرفتن زمان توقف ماشین و زمان تعمیر آن، که انطباق با محیط صنعت داشته باشد، توسعه داده شده است. برای یافتن جواب الگوریتم پرندگان فاخته چند هدفه توسعه داده شده است أکثردر این مقاله یک مدل جدید زمان بندی ماشین با در نظر گرفتن امکان پذیری حمل، وابستگی زمان حمل به نوع کار، در نظر گرفتن زمان توقف ماشین و زمان تعمیر آن، که انطباق با محیط صنعت داشته باشد، توسعه داده شده است. برای یافتن جواب الگوریتم پرندگان فاخته چند هدفه توسعه داده شده است و جهت مقایسه و تست کارایی آن از دو الگوریتم دیگر با همان ساختار جواب استفاده شده است. نتایج بدست آمده که توسط الگوریتم جدید پرندگان فاخته چند هدفه توسعه داده شده استخراج شده است را با الگوریتم های دیگر مقایسه گردید و نتایج بدست آمده نشان دهنده برتری کیفیت جوابهای الگوریتم پرندگان فاخته چند هدفه توسعه داده شده برای حل این نوع مساله می باشد. لذا بکارگیری این مساله جدید با روش حل پیشنهادی در محیط صنعت باعت کاهش همزمان هزینه ها و افزایش سطح کیفیت و افزایش سطح خدمت رسانی به مشتریان می‌گردد. تفاصيل المقالة -
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32 - شناسایی و رتبه‌بندی شاخص های موثر بر مسیریابی و زمانبندی حملونقل شهری پایدار با استفاده از تصمیم‌گیریهای چندمعیاره
shiba masoumi Seyyed Mohammad Hadji Molana Mehrdad Javadi Amir Aziziچکیدهمطالعه حاضر با روش شناسی توصیفی- تحلیلی و استفاده از روشهای دلفی، بهترین-بدترین و بهترین اولویت، با هدف ارزیابی و رتبه‌بندی شاخص‌های پایداری حملونقل شهری انجام گرفته است. جهت دستیابی به شاخص‌های حملونقل پایدار در سه بعد اقتصادی، اجتماعی و زیست محیطی، رتبه‌بندی أکثرچکیدهمطالعه حاضر با روش شناسی توصیفی- تحلیلی و استفاده از روشهای دلفی، بهترین-بدترین و بهترین اولویت، با هدف ارزیابی و رتبه‌بندی شاخص‌های پایداری حملونقل شهری انجام گرفته است. جهت دستیابی به شاخص‌های حملونقل پایدار در سه بعد اقتصادی، اجتماعی و زیست محیطی، رتبه‌بندی معیارها براساس مطالعات کتابخانه‌ای، و نظر خبرگان انجام گرفت تا فقط معیارهایی که از اهمیت زیادی بر روی مسئله پژوهش برخودار هستند، وارد روش دلفی شده و با صرفه‌جویی در زمان و تعداد رفت و برگشت کمتری، معیارهای ارزیابی، نهایی گردند. معیارهای نهایی با استفاده از روش بهترین- بدترین و روش بهترین اولویت، وارد فرآیند وزن‌دهی و رتبه‌بندی شدند. مقایسه نتایج دو روش بهترین-بدترین و بهترین اولویت با استفاده از روشهای آماری انجام شد و با توجه به اینکه رتبه‌بندی معیارها در هر دو روش یکسان شد و ضریب همبستگی اسپیرمن 1+ بدست آمد، پس همبستگی قوی بین معیارها برقرار است، ضریب همبستگی پبرسون جهت مقایسه وزنها 0/989و میزان معنی داری صفر بدست آمد که نشان دهنده رابطه قوی بین متغیر ها است . لذا رتبه‌بندی و وزن‌دهی حاصل از دو روش مورد قبول واقع شد. تفاصيل المقالة -
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33 - حل مساله تبادل زمان ـ هزینه ـ کیفیت پروژه‌ها در حالت احتمالی با در نظرگرفتن راه حل های ممکن
S. Farid Mousavi Kaveh Khalili-Damghani Farnaz Rezapour Arezoo Gazori-Nishaboriمدیران پروژه همواره به دنبال اتخاذ تصمیماتی هستند که بتوانند پروژه‌های خود را در کوتاه‌ترین زمان ممکن، با کمترین هزینه و با کیفیتی بالا به انجام برسانند. لیکن باید توجه داشت که در مسائل واقعی با شرایطی مواجه می‌شویم که پیش‌بینی‌های ما تحت تاثیر سایر عوامل از آنچه در عمل أکثرمدیران پروژه همواره به دنبال اتخاذ تصمیماتی هستند که بتوانند پروژه‌های خود را در کوتاه‌ترین زمان ممکن، با کمترین هزینه و با کیفیتی بالا به انجام برسانند. لیکن باید توجه داشت که در مسائل واقعی با شرایطی مواجه می‌شویم که پیش‌بینی‌های ما تحت تاثیر سایر عوامل از آنچه در عمل اتفاق می‌افتد فاصله میگیرد در چنین شرایطی عملاً برخی یا تمامی پارامترهای مرتبط با یک مساله مورد بررسی به وسیله متغیرهایی بیان می‌شوند که به صورت قطعی تعریف نشده‌اند. از این رو در نظر گرفتن اثر پارامترهای تصادفی در حل مساله تبادل زمان ـ هزینه ـ کیفیت دارای اهمیت بسیار زیادی میباشد. در این مقاله سعی داریم تا مدل مساله تبادل زمان ـ هزینه ـ کیفیت ارائه شده را در حالت تصادفی مورد توجه قرار دهیم. به این منظور برخی از پارامترهای مدل مورد اشاره را به صورت تصادفی فرض می‌کنیم. سپس به منظور حل مدل تصادفی از رویکرد برنامهریزی مقید شده تصادفی استفاده خواهیم کرد. به هنگام مواجهه با توابع هدف چندگانه از میان روشهای بهینه‌سازی مسائل چندهدفه به روش برنامهریزی آرمانی خواهیم پرداخت و در نهایت مدل برنامهریزی آرمانی مقید شده تصادفی را ارائه خواهیم نمود. معدل برنامه ریزی قطعی مدل ارائه شده ارائه میشود و در نهایت با استفاده از نرم افزار گمز و با یک مثال عددی، مدل ارائه شده حل و نتایج حاصل از آن مورد بررسی قرار خواهد گرفت. تفاصيل المقالة -
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34 - ارائه روشی جهت تعیین اندازه بافرها در حوزه زمان بندی زنجیره بحرانی (مطالعه موردی: شرکت سولیران)
Mohammad Mehdi Tavagho Hamedani Ahmad Makouieزنجیره بحرانی رویکردی نوین در حوزه مدیریت پروژه می باشد که به منظور رفع اثرات نامطلوب پروژه ها و علل بروز آنها، افزایش کارایی منابع و بهره برداری از محدودیتهای سیستم پروژه توسعه یافته است. بر مبنای این رویکرد و به منظور ایمن کردن پروژه در مقابل اختلالات احتمالی، بافرهای أکثرزنجیره بحرانی رویکردی نوین در حوزه مدیریت پروژه می باشد که به منظور رفع اثرات نامطلوب پروژه ها و علل بروز آنها، افزایش کارایی منابع و بهره برداری از محدودیتهای سیستم پروژه توسعه یافته است. بر مبنای این رویکرد و به منظور ایمن کردن پروژه در مقابل اختلالات احتمالی، بافرهای زمانی در محل‌های مختلف تعبیه میشود. بنابراین از انتقال تنشهای فعالیتهای غیر بحرانی به زنجیره بحرانی و همچنین انتقال تنشهای فعالیتهای زنجیره بحرانی به زمان تحویل پروژه جلوگیری میشود. در این مقاله روشی جهت تعیین اندازه بافرها در حوزه زمانبندی زنجیره بحرانی ارائه شده که از جمله ویژگی های آن اعمال نظر خبرگان در مراحل کار و سادگی اجرا میباشد. مفاهیم مطرح شده در این روش نزدیک به روش پرت می باشد با این تفاوت که در این روش تابع توزیع احتمال زمان فعالیت‌ها براساس نظرات خبرگان بدست آمده است. در پایان جهت ارزیابی روش پیشنهادی، زنجیره بحرانی جهت پروژه طراحی، ساخت و نصب سازه ای فولادی در شرکت سولیران به اجرا درآمد. اندازه بافرها با استفاده از دو روش شناخته شده در ادبیات موضوع (روش بریدن و چسباندن و روش ریشه مربع خطا) و روش پیشنهادی محاسبه گردید. نتایج بدست آمده مبین آن است که روش ارائه شده در مقایسه با دو روش مذکور بافرهایی با محافظت بیشتر در برابر تأخیرهای احتمالی پروژه ایجاد می‌کند. تفاصيل المقالة -
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35 - بکارگیری رویه جستجوی تصادفی تطابقی حریصانه برای زمانبندی مسئله جریان کارگاهی بدون صف های میانی با استفاده از تبدیل به مسئله فروشنده دوره گرد
Javad Behnamian Ronak Mohammadi Omid Rezaeiهدف از این مقاله یافتن توالی بهینه به منظور کمینه کردن فاصله زمانی ساخت برای مسئله زمانبندی جریان کارگاهی بدون صفهای میانی میباشد. مسائل زمانبندی بدون انتظار در آن دسته از محیطهای تولیدی رخ میدهد که در آن یک کار میبایست از آغاز تا پایان بر روی یک ماشین یا چند ماشین بدون أکثرهدف از این مقاله یافتن توالی بهینه به منظور کمینه کردن فاصله زمانی ساخت برای مسئله زمانبندی جریان کارگاهی بدون صفهای میانی میباشد. مسائل زمانبندی بدون انتظار در آن دسته از محیطهای تولیدی رخ میدهد که در آن یک کار میبایست از آغاز تا پایان بر روی یک ماشین یا چند ماشین بدون وقفه پردازش شود. از آنجایی که ساختار این مسئله شباهت بسیاری با مسئله فروشنده دورهگرد دارد، در تحقیق حاضر از یک رویکرد جدید جهت بدست آوردن دیرکردها کمک گرفته شده به گونه ای که با هدف یافتن توالی بهینه عملیاتی که کمترین فاصله زمانی ساخت را داراست از ماتریس دیرکردهای بدست آمده از مسئله فروشنده دورهگرد استفاده شده است. همچنین از الگوریتم جستجوی تصادفی تطابقی حریصانه برای حل مسئله تعیین توالی جریان کارگاهی بدون صفهای میانی استفاده و کارایی آن پس از تعیین پارامتر از طریق روش فاکتوریل، با الگوریتم کلونی مورچگان مقایسه شده است. تفاصيل المقالة -
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36 - ارائه مدل زمانبندی استوار پروژه با منابع محدود و حل آن با استفاده از الگوریتم فرا ابتکاری بهینه سازی انبوه ذرات (مطالعه موردی: پالایشگاه میعانات گازی بندر عباس)
Mohammadhusein Nabizadeh Huseinali Hasanpoor Roozbeh Azizmohammadi Navid Hashtroodiانجام فعالیت های پروژه مطابق برنامه زمان بندی یکی از مسائل مورد توجه دست اندرکاران پروژه ها به ویژه مدیران پروژه ها می باشد. همچنین ماهیت بسیار دشوار این مسئله، علت دیگری برای توجه زیاد محققین به آن میباشد. بنابراین تکنیک ها و روشهای خاصی برای حل این مسائل مطرح شده‌ان أکثرانجام فعالیت های پروژه مطابق برنامه زمان بندی یکی از مسائل مورد توجه دست اندرکاران پروژه ها به ویژه مدیران پروژه ها می باشد. همچنین ماهیت بسیار دشوار این مسئله، علت دیگری برای توجه زیاد محققین به آن میباشد. بنابراین تکنیک ها و روشهای خاصی برای حل این مسائل مطرح شده‌اند. از اینرو توجه بیشتر به پایداری زمانبندی پروژه برای مدیران پروژه موضوعیت دارد. در این مقاله برای یک مسئله واقعی زمانبندی پروژه پالایشگاهی ابتدا مدل زمانبندی پایدار ارائه‌شده و به دلیل اینکه زمانبندی پروژه با محدودیت منابع از جمله مسائل NP-Hard است، الگوریتم فرا ابتکاری بهینه سازی انبوه ذرات برای حل این مسئله پیشنهاد شده است. به منظور اعتبارسنجی مدل نیز 4 مسئله با ابعاد کوچک انتخاب و جوابهای به دست آمده از الگوریتم‌های پیشنهادی با جواب دقیق به دست آمده حاصل از نرم‌افزار Lingo مقایسه گردیده است. نتایج به دست آمده نشان می دهد الگوریتم پیشنهادی کارا و همگرا به جواب بهینه می‌باشند. تفاصيل المقالة -
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37 - حل مسئله زمانبندی پروژه با محدودیت منابع چندهدفه در حالت چند مد با الگوریتم زنبورهای عسل چندهدفه
Amir Sadeghi Sina Namazi Zahra Ghorajehlo Behnam Rezvanpourمساله زمانبندی پروژه با منابع محدود، در واقع کلی ترین مساله زمانبندی است. مسائل زمانبندی کارگاهی ، جریان کارگاهی ، زمانبندی و سایر مسائل زمانبندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. در این مقاله مسئله زمانبندی پروژه با محدودیت منابع در حالت چند مد و رو أکثرمساله زمانبندی پروژه با منابع محدود، در واقع کلی ترین مساله زمانبندی است. مسائل زمانبندی کارگاهی ، جریان کارگاهی ، زمانبندی و سایر مسائل زمانبندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. در این مقاله مسئله زمانبندی پروژه با محدودیت منابع در حالت چند مد و روابط پیش نیازی جزئی در حالت مدل چندهدفه پیشنهاد شده است. در جهت کاربردی تر کردن بیش از پیش این مسئله مشهور اهداف مهم و کاربردی از قبیل کمینه کردن زمان اتمام پروژه و بیشینه کردن کیفیت انجام فعالیت های پروژه و کمینه کردن هزینه کل پروژه در نظر گرفته شده است. پس از اعتبار دهی مدل با استفاده از الگوریتم زنبورهای عسل به حل این مدل چند هدفه پیشنهادی، پرداخته شده است و نتایج عملکرد، با الگوریتم NSGA-II مقایسه شده است. نتایج نشان دهنده این است که الگوریتم پیشنهادی عملکرد مناسبی در حل این گونه مسائل داشته است. تفاصيل المقالة -
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38 - حل مسئله زمانبندی پروژه با هدف کمینه سازی زمان اتمام پروژه با محدودیت منابع با الگوریتم فراابتکاری قورباغه
Alireza Haji Akhondi Gholam Reza Tavakoli Peyman Akhavan Manouchehr Manteghiالگوریتم جهش ترکیبی قورباغه (SFLA) یک الگوریتم مبتنی بر ممتیک متاهیوریستیکِ است. این الگوریتم در سالهای اخیر توسط Eusuff و Lansey ایجاد شد. الگوریتم SFLA از نحوه‌ی جستجوی غذای گروه‌های قورباغه سرچشمه میگیرد. این الگوریتم برای جستجوی محلی میان زیرگروه‌های قورباغه از رو أکثرالگوریتم جهش ترکیبی قورباغه (SFLA) یک الگوریتم مبتنی بر ممتیک متاهیوریستیکِ است. این الگوریتم در سالهای اخیر توسط Eusuff و Lansey ایجاد شد. الگوریتم SFLA از نحوه‌ی جستجوی غذای گروه‌های قورباغه سرچشمه میگیرد. این الگوریتم برای جستجوی محلی میان زیرگروه‌های قورباغه از روش نمو ممتیک استفاده می‌کند. SFLA از استراتژی ترکیب استفاده می‌کند و امکان مبادله پیام در جستجوی محلی را فراهم می‌سازد. الگوریتم جهش ترکیبی قورباغه مزایای الگوریتم نمو ممتیک و بهینه‌سازی گروه ذرات (PSO) را ترکیب می‌کند. یکی از مسائل مشهور در زمینه کنترل پروژه، زمانبندی پروژه با محدودیت منابع و سایر محدودیتها می باشد که زمانبندی پروژه با در نظر گرفتن محدودیت منابع از جمله مسائل دارای پیشینه تحقیقاتی غنی است. مساله زمانبندی پروژه با منابع محدود در واقع کلی ترین مساله زمانبندی است. مسائل زمانبندی کارگاهی، جریان کارگاهی ، زمانبندی و سایر مسائل زمانبندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. زمانبندی پروژه یکی از وظایف اصلی و فعالیتهای اصلی در مدیریت پروژه است. وجود محدودیت منابع و همچنین روابط پیش نیازی بین فعالیت‌ها مسئله زمانبندی پروژه را امری دشوار می‌سازد. زمانبندی پروژه با در نظر گرفتن محدودیت منابع از جمله مسائل با ادبیات غنی در حوزه مسائل تحقیق در عملیات است.این مسئله توجه محققان را در سالهای اخیر بشدت بخود جلب کرده است و تاکنون با الگوریتم های مختلف حل شده است. در این مقاله به بررسی و عملکرد الگوریتم جهش قورباغه (SFLA) در حل مسائل زمانبندی پروژه با محدودیت منابع پایه پرداخته می شود که نتایج حاکی از عملکرد مناسب و قوی این الگوریتم فراابتکاری جدید می باشد. تفاصيل المقالة -
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39 - مقایسه کارایی روش های "سیستم کلونی مورچگان" و "برنامه ریزی خطی" در مدل سازی مسأله زمان- بندی تولید جریانی
Said Esfandyari Ali Morovati Sharif Abadi Seyed Habibolah Mirghafouri Hamid Reza Kadkhodazadehهر چند که برنامه ریزی خطی در دنیای واقع کاربردهای زیادی دارد، اما در برخورد با مسائل پیچیده و سخت عدم کارایی خود را نشان داده است. با پیشرفت علم و رویارویی با مشکلات مختلف، تمایل به حل مسائل در حجم زیاد در زمان کوتاه بیشتر شده است. روش های ابتکاری و فوق ابتکاری جدیدترین أکثرهر چند که برنامه ریزی خطی در دنیای واقع کاربردهای زیادی دارد، اما در برخورد با مسائل پیچیده و سخت عدم کارایی خود را نشان داده است. با پیشرفت علم و رویارویی با مشکلات مختلف، تمایل به حل مسائل در حجم زیاد در زمان کوتاه بیشتر شده است. روش های ابتکاری و فوق ابتکاری جدیدترین دستاورد برنامه ریزی غیرخطی در حل این گونه مسائل هستند. یکی از حوزه هایی که نیاز به برنامه ریزی در حجم بالا دارد زمان بندی تولید در مسائل سخت می باشد. این مقاله به مدل سازی و مقایسه دو روش برنامه ریزی خطی و الگوریتم سیستم مورچگان در زمان بندی تولید جریانی منعطف با توجه به متغیرهای تعداد ماشین و سفارش پرداخته است؛ مبنای مقایسه در این پژوهش شاخص های زمان پردازش، تعداد محدودیت، بهینگی و حجم حافظه اشغال شده مربوط به اعداد تصادفی می باشد. در این مقاله از روش پژوهششبه آزمایشی استفاده شده است، ابزار آزمایش به ترتیب نرم افزارهای سی شارپ و لینگو برای الگوریتم مورچگان و برنامه ریزی خطی است. نتایج به دست آمده نشان می دهد که مدل برنامه ریزی خطی درتعداد ماشین و سفارش پایین کارایی بالاتری دارد، اما با افزایش ماشین و سفارش با توجه به شاخص های در نظر گرفته شده، الگوریتم سیستم مورچگان کارایی بالاتر خود را نشان می دهد. تفاصيل المقالة -
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40 - کمینه‌سازی انحراف از عیارهای حد در برنامهریزی تولید بلند مدت معادن روباز با هدف کنترل انباشتگاه باطله
احسان موسوی رضا شیرین آبادیهدف اساسی برنامه ریزی تولید بلند مدت، اتخاذ تدابیری جهت اجرای عیارهای حد استخراجی و برنامهریزی تولید کوتاه مدت است. روش های ارائه شده حاکی از عدم توجه به تنظیم دقیق عیار استخراجی در بازه های زمانی مختلف است. لزوم بهینه سازی عیارهای حد استخراجی در برنامه ریزی تولید بلند أکثرهدف اساسی برنامه ریزی تولید بلند مدت، اتخاذ تدابیری جهت اجرای عیارهای حد استخراجی و برنامهریزی تولید کوتاه مدت است. روش های ارائه شده حاکی از عدم توجه به تنظیم دقیق عیار استخراجی در بازه های زمانی مختلف است. لزوم بهینه سازی عیارهای حد استخراجی در برنامه ریزی تولید بلند مدت، مدیریت صحیح کانسنگ ارسالی به کارخانه فرآوری بلحاظ کیفیت مطلوب است. از سویی دیگر، انتخاب مطلوب و بهینه عیارهای حد در معادن روباز، موجبات کنترل انباشتگاه مواد معدنی و نیز جلوگیری از عواقب ناشی از پساب های مواد معدنی را بسبب مسائل محیط زیست، منتج خواهد شد. در این مقاله، مدل برنامه ریزی خطی جهت تعیین توالی استخراج بلوک ها با توجه به کنترل عیارهای حد استخراجی ارائه شده است. هدف از مدل ارائه شده، کمینه سازی انحراف عیارهای استخراجی در دوره های برنامه ریزی است. این مهم سبب می شود که عیارهای استخراجی در هر دورۀ زمانی بر اساس عیار مورد پذیرش کارخانه مورد تنظیم دقیق قرار گیرند. به منظور اعتبارسنجی از مدل پیشنهادی، معدن آهن چادرملو به عنوان مورد مطالعاتی انتخاب شده است. نتایج نشان می دهد عیارهای حد استخراجی بدست آمده از مدل پیشنهادی، متوسط عیار مورد پذیرش کارخانه فرآوری را در هر دورۀ برنامه ریزی با دقت بالایی مورد لحاظ قرار داده است. تفاصيل المقالة -
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41 - کمینه‌سازی انحراف از عیارهای حد بهینه در برنامهریزی تولید بلند مدت معادن روباز با استفاده از برنامهریزی عدد صحیح مختلط
احسان موسوی رضا شیرین آبادیهدف اساسی برنامه ریزی تولید بلند مدت، اتخاذ تدابیری جهت اجرای عیارهای حد استخراجی و برنامهریزی تولید کوتاه مدت است. از این رو، عیارهای حد استخراجی، مهمترین ابزار اجرای راهبردی و برنامه ای بلند مدت در معادن روباز بشمار می روند. روش های ارائه شده حاکی از عدم توجه به تنظی أکثرهدف اساسی برنامه ریزی تولید بلند مدت، اتخاذ تدابیری جهت اجرای عیارهای حد استخراجی و برنامهریزی تولید کوتاه مدت است. از این رو، عیارهای حد استخراجی، مهمترین ابزار اجرای راهبردی و برنامه ای بلند مدت در معادن روباز بشمار می روند. روش های ارائه شده حاکی از عدم توجه به تنظیم دقیق عیار استخراجی در بازه های زمانی مختلف است. لزوم بهینه سازی عیارهای حد استخراجی در برنامه ریزی تولید بلند مدت، مدیریت صحیح کانسنگ ارسالی به کارخانه فرآوری بلحاظ کیفیت مطلوب است. در این مقاله، مدل برنامه ریزی خطی جهت تعیین توالی استخراج بلوک ها با توجه به کنترل عیارهای حد استخراجی ارائه شده است. مدل برنامه ریزی تولید بلند مدت با استفاده از برنامه ریزی ریاضی عدد صحیح مختلط فرموله شده است. هدف از مدل ارائه شده، کمینه سازی انحراف عیارهای استخراجی در دوره های برنامه ریزی است. این مهم سبب می شود که عیارهای استخراجی در هر دورۀ زمانی بر اساس عیار مورد پذیرش کارخانه مورد تنظیم دقیق قرار گیرند. به منظور اعتبارسنجی از مدل پیشنهادی، معدن آهن چادرملو به عنوان مورد مطالعاتی انتخاب شده است. نتایج نشان می دهد عیارهای حد استخراجی بدست آمده از مدل پیشنهادی، متوسط عیار مورد پذیرش کارخانه فرآوری را در هر دورۀ برنامه ریزی با دقت بالایی مورد لحاظ قرار داده است. همچنین تمام محدودیت های عملیاتی موجود برآورده شده است. تفاصيل المقالة -
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42 - Improving Energy-Efficient Target Coverage in Visual Sensor Networks
Behrooz Shahrokhzadeh Mehdi Dehghan MohammadReza ShahrokhzadehTarget coverage is one of the important problems in visual sensor networks. The coverage should be accompanied with an efficient use of energy in order to increase the network lifetime. In this paper, we address the maximum lifetime for visual sensor networks (MLV) prob أکثرTarget coverage is one of the important problems in visual sensor networks. The coverage should be accompanied with an efficient use of energy in order to increase the network lifetime. In this paper, we address the maximum lifetime for visual sensor networks (MLV) problem by maximizing the network lifetime while covering all the targets. For this purpose, we develop a simulated annealing (SA) algorithm that divides the sensors’ Field-of-View (FoV) to a number of cover sets and then applies a sleep-wake schedule for cover sets. We also identify the best possible FoV of sensors according to the targets’ location using rotating cameras, to reduce the solution space and approaching to a near-optimal solution. Our proposed energy and neighbor generating functions of the SA result in a balanced distribution of energy consumption as well as escaping from local optima. We conduct some simulation experiments to evaluate the performance of our proposed method by comparing with some well-known solutions in the literature. تفاصيل المقالة -
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43 - برنامه ریزی خطوط هواپیمایی با در نظر گرفتن محدودیتهای عملیاتی
شکوه خردمند محمد محمدی بهمن نادریاز گذشته تا به امروز به علت بالا بودن هزینههای مربوط به صنعت هوایی و هواپیماها، برنامهریزی برای این صنعت از اهمیت زیادی برخوردار بوده است. یکی از مسائل مربوط به صنعت هوایی، مسئله‌ی مسیریابی هواپیماها و تعیین تعداد هواپیماهای مورد نیاز در هر برنامه‌ی پروازی است. این مس أکثراز گذشته تا به امروز به علت بالا بودن هزینههای مربوط به صنعت هوایی و هواپیماها، برنامهریزی برای این صنعت از اهمیت زیادی برخوردار بوده است. یکی از مسائل مربوط به صنعت هوایی، مسئله‌ی مسیریابی هواپیماها و تعیین تعداد هواپیماهای مورد نیاز در هر برنامه‌ی پروازی است. این مسائل، بخش قابل توجهی از هزینههای صنعت هوایی را برعهده دارند. از طرفی با توجه به یک سری محدودیتها و قوانینی که شرکت‌های هواپیمایی در برنامههای پروازی برای هر هواپیما دارند، به دست آوردن یک برنامه‌ی پروازی مناسب به منظور تعیین تعداد هواپیماهای مورد نیاز، کمینه سازی هزینههای مربوط به هواپیماها و هزینههای ناشی از فروش از دست رفته دارای اهمیت زیادی است. از طرفی با توجه به NP-hard بودن این مسئله، حل دقیق مدل در سایزهای بزرگ امکان پذیر نمی‌باشد؛ لذا با کمک الگوریتم‌های فراابتکاری چون ژنتیک و شبیه سازی تبرید به حل مسئله در سایزهای بزرگ پرداختیم و نتایج حاصل از آنها را با یکدیگر مقایسه کردیم و در نتیجه به برتری الگوریتم شبیه سازی تبرید نسبت به الگوریتم ژنتیک رسیدیم. تفاصيل المقالة -
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44 - An Integrated Model of Project Scheduling and Material Ordering: A Hybrid Simulated Annealing and Genetic Algorithm
Nima Zoraghi Amir Abbas Najafi سید تقی اخوان نیاکیThis study aims to deal with a more realistic combined problem of project scheduling and material ordering. The goal is to minimize thetotal material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject أکثرThis study aims to deal with a more realistic combined problem of project scheduling and material ordering. The goal is to minimize thetotal material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject tosome constraints. The problem is first mathematically modelled. Then a hybrid simulated annealing and genetic algorithm is proposed tosolve it. In addition, some experiments are designed and the Taguchi method is employed to both tune the parameters of the proposedalgorithm and to evaluate its performance. The results of the performance analysis show the efficiency of the proposed methodology. تفاصيل المقالة -
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45 - A Hierarchical Production Planning and Finite Scheduling Framework for Part Families in Flexible Job-shop (with a case study)
Davod Abachi fariborz jolai hasan halehTendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, أکثرTendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate production planning in medium-term timeframe with scheduling in short-term timeframe. Our contribution creates production planning and scheduling framework in flexible job shop environment with respect to time-limit of each machine in order to produce different parts families in automotive industry. Production planning and scheduling have iterative relationship. In this strategy information flow is transformed reciprocative between production planning and scheduling for satisfying time-limit of each machine. The proposed production planning has heuristic approach and renders a procedure to determine production priority of different part families based on safety stock. Scheduling is performed with ant colony optimization and assigns machine in order of priority to different part families on each frozen horizon. Results showed that, the proposed heuristic algorithm for planning decreased parts inventory at the end of planning horizon. Also, results of proposed ant colony optimization was near the optimal solution .The framework was performed to produce sixty four different part families in flexible job-shop with fourteen different machines. Output from this approach determined volume of production batches for part families on each frozen horizon and assigned different operations to machines. تفاصيل المقالة -
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46 - Scheduling of a flexible flow shop with multiprocessor task by a hybrid approach based on genetic and imperialist competitive algorithms
Javad Rezaeian Hany Seidgar Morteza KianiThis paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Thre أکثرThis paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA and ICA are proposed to solve the generated problems. The performances of algorithms are evaluated by computational time and Relative Percentage Deviation (RPD) factors. The results indicate that ICA solves the problems faster than other algorithms and the hybrid algorithm produced best solution based on RPD. تفاصيل المقالة -
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47 - The project portfolio selection and scheduling problem: mathematical model and algorithms
Bahman NaderiThis paper investigates the problem of selecting and scheduling a set of projects among available projects. Each project consists of several tasks and to perform each one some resource is required. The objective is to maximize total benefit. The paper constructs a mathe أکثرThis paper investigates the problem of selecting and scheduling a set of projects among available projects. Each project consists of several tasks and to perform each one some resource is required. The objective is to maximize total benefit. The paper constructs a mathematical formulation in form of mixed integer linear programming model. Three effective metaheuristics in form of the imperialist competitive algorithm, simulated annealing and genetic algorithm are developed to solve such a hard problem. The proposed algorithms employ advanced operators. The performance of the proposed algorithms is numerically evaluated. The results show the high performance of the imperialist competitive algorithm outperforms the other algorithms. تفاصيل المقالة -
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48 - An Assessment Method for Project Cash Flow under Interval-Valued Fuzzy Environment
Vahid Mohagheghi SEYED meysam mousavi Behnam VahdaniEffective project management requires reliable knowledge of cash required in different stages of project life cycle. Getting this knowledge is highly dependent on sophisticated consideration of project environment. Nature of projects and their environments are associate أکثرEffective project management requires reliable knowledge of cash required in different stages of project life cycle. Getting this knowledge is highly dependent on sophisticated consideration of project environment. Nature of projects and their environments are associated with uncertain conditions. In this paper, a new project cash flow assessment method based on project scheduling is proposed to foresee projects' cash flow in their different stages. Interval-valued fuzzy sets (IVFSs) are applied to address the uncertainty of activity durations and costs. First, an IVF-project scheduling method is proposed to calculate early start time and early finish time of activities under IVF-environment and based on that, a new method of cash flow assessment is introduced under IVF-environment. For the purpose of illustration, the proposed method is implemented to generate cash flow of main activities of a large-scale project. The results show the flexibility of presented assessment method in expressing uncertainty, in addition to its capability in risk evaluation. Furthermore, using alpha-cuts to address different levels of uncertainty and risk provides a comprehensive insight of the cash required in different stages of project life cycle under different levels of risk and uncertainty. Finally, the results are discussed and the proposed method is believed to be useful in the project evaluation. تفاصيل المقالة -
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49 - Modeling and scheduling no-idle hybrid flow shop problems
Mehdi Yazdani Bahman NaderiAlthough several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the prob أکثرAlthough several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the problem of scheduling no-idle hybrid flow shops. A mixed integer linear programming model is first developed to mathematically formulate the problem. Using commercial software, the model can solve small instances to optimality. Then, two metaheuristics based on variable neighborhood search and genetic algorithms are developed to solve larger instances. Using numerical experiments, the performance of the model and algorithms are evaluated.Although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the problem of scheduling no-idle hybrid flow shops. A mixed integer linear programming model is first developed to mathematically formulate the problem. Using commercial software, the model can solve small instances to optimality. Then, two metaheuristics based on variable neighborhood search and genetic algorithms are developed to solve larger instances. Using numerical experiments, the performance of the model and algorithms are evaluated. تفاصيل المقالة -
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50 - Scheduling of Multiple Autonomous Guided Vehicles for an Assembly Line Using Minimum Cost Network Flow
Hamed FazlollahtabarThis paper proposed a parallel automated assembly line system to produce multiple products having multiple autonomous guided vehicles (AGVs). Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the as أکثرThis paper proposed a parallel automated assembly line system to produce multiple products having multiple autonomous guided vehicles (AGVs). Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs. Scheduling of AGVs to service the assembly lines and the corresponding stations are purposed. In the proposed problem the assignment of multiple AGVs to different assembly lines and the stations are performed using minimum-cost network flow (MCF). It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as MCF problem during each short-term scheduling window. تفاصيل المقالة -
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51 - New Heuristic Algorithm for Flow Shop Scheduling with 3 Machines and 2 Robots Considering the Breakdown Interval of Machines and Robots Simultaneously
mahdi eghbali Mohammad Saidi Mehrabad hassan halehScheduling is an important subject of production and operations management area. In flow-shop scheduling, the objective is to obtain a sequence of jobs which when processed in a fixed order of machines, will optimize some well defined criteria. The concept of transporta أکثرScheduling is an important subject of production and operations management area. In flow-shop scheduling, the objective is to obtain a sequence of jobs which when processed in a fixed order of machines, will optimize some well defined criteria. The concept of transportation time is very important in scheduling. Transportation can be done by robots. In situations that robots are used to transport materials (material handler), breakdown of the machines and robots have a significant role in the production concern. This paper deals with minimization of the total elapsed time for flow shop scheduling problem (number of machine=3) in which the effect of machine and robots breakdown interval are considered simultaneously. Furthermore, by providing an example, the proposed algorithm is described. A summary and future works conclude the paper تفاصيل المقالة -
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52 - A Job Shop Scheduling and Location of Battery Charging Storage for the Automated Guided Vehicles (AGVs)
Saeed Dehnavi-Arani Ali Sabaghian Mehdi FazliWhen the Automated Guided Vehicles (AGVs) are transferring the parts from one machine to another in a job shop environment, it is possible that AGVsstopon their guidepaths since their batteries are discharged.Consequently, it is essential to establish at least one Batte أکثرWhen the Automated Guided Vehicles (AGVs) are transferring the parts from one machine to another in a job shop environment, it is possible that AGVsstopon their guidepaths since their batteries are discharged.Consequently, it is essential to establish at least one Battery Charging Storage (BCS) to replace full batteries with empty batteries for the stopped AGVs. Due to non-predictable routes for AGVs in the manufacturing systems, to find the best place toestablish the BCS can impact performance of the system. In this paper, anintegrated mathematical modelof job shop and AGV schedulingwith respect tothe location of a BCS is proposed. The proposed nonlinear model is transformed into a linear form to beefficiently solvedin GAMS software. Finally, several numerical examplesare presented to test the validity of the proposed mathematical model.The results show that the optimal cost and location of BCS can be obtained with respect to the number of AGVs, machines, parts, and other problem parameters. In addition, it is concluded that the increasing number of AGVs in a manufacturing systemcannot be always a suitable policy for reducing the cost because in such conditions.Further to that, the conflict of AGVs may increase leading tothe increase of the makespan. In other words, following the optimal point, increasing AGVs leads to the increase in costs. تفاصيل المقالة -
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53 - Diversified Particle Swarm Optimization for Hybrid Flowshop Scheduling
Javad BehnamianThe aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm أکثرThe aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society whose members behave anarchically to improve their situations. Such anarchy lets the algorithm explore the solution space perfectly and prevent falling in the local optimum traps. Besides, for the first time, for the hybrid flowshop, we proposed eight different local search algorithms and incorporate them into the algorithm in order to improve it with the help of systematic changes of the neighborhood structure within a search for minimizing the makespan. The proposed algorithm was tested and the numerical results showe that the proposed algorithm significantly outperforms other effective heuristics recently developed. تفاصيل المقالة -
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54 - A Mathematical Model and a Solution Method for Hybrid Flow Shop Scheduling
Esmaeil Najafi Bahman Naderi Hassan Sadeghi Mehdi YazdaniThis paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, theproblem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithmhyb أکثرThis paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, theproblem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithmhybridized with a simple local search in form of simulated annealing is proposed. Two experiments are carried out to evaluate the modeland the algorithm. In the first one, the general performance of the model and the proposed algorithm is experimented. In the next one, thepresented algorithm is compared against some other algorithms. The results support high performance of the proposed algorithm. تفاصيل المقالة -
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55 - Project Portfolio Selection with the Maximization of Net Present Value
Mostafa Nikkhah Nasab Amir Abbas NajafiProjects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. An integer programming model is formulated for the project portfolio selection and scheduling.Tw أکثرProjects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. An integer programming model is formulated for the project portfolio selection and scheduling.Two heuristic algorithms, genetic algorithm (GA) and simulated annealing (SA), are presented to solve the problem. Results of calculations show that the algorithm performance of GA is better than SA in project portfolio selection to maximize the NPV of the project portfolio. تفاصيل المقالة -
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56 - َA Multi-objective simulated annealing algorithm to solving flexible no-wait flowshop scheduling problems with transportation times
Bahman Naderi Hassan SadeghiThis paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in أکثرThis paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective simulated annealing algorithm (MOSA). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOSA provides sound performance comparing with other algorithms. تفاصيل المقالة -
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57 - Design of a Hybrid Genetic Algorithm for Parallel Machines Scheduling to Minimize Job Tardiness and Machine Deteriorating Costs with Deteriorating Jobs in a Batched Delivery System
Mohammad Saidi-Mehrabad Samira BairamzadehThis paper studies the parallel machine scheduling problem subject to machine and job deterioration in a batched delivery system. By the machine deterioration effect, we mean that each machine deteriorates over time, at a different rate. Moreover, job processing times a أکثرThis paper studies the parallel machine scheduling problem subject to machine and job deterioration in a batched delivery system. By the machine deterioration effect, we mean that each machine deteriorates over time, at a different rate. Moreover, job processing times are increasing functions of their starting times and follow a simple linear deterioration. The objective functions are minimizing total tardiness, delivery, holding and machine deteriorating costs. The problem of total tardiness on identical parallel machines is NP-hard, thus the under investigation problem, which is more complicated, is NP-hard too. In this study, a mixed-integer programming (MILP) model is presented and an efficient hybrid genetic algorithm (HGA) is proposed to solve the concerned problem. A new crossover and mutation operator and a heuristic algorithm have also been proposed depending on the type of problem. In order to evaluate the performance of the proposed model and solution procedure, a set of small to large test problems are generated and results are discussed. The related results show the effectiveness of the proposed model and GA for test problems. تفاصيل المقالة -
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58 - A Bi-Objective Airport Gate Scheduling with Controllable Processing Times Using Harmony Search and NSGA-II Algorithms
Morteza khakzar Bafruei Sananz khatibi Morteza RahmaniOptimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this أکثرOptimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this research line shows thatin almost all studies airport gate processing time has been considered as a fix parameter. In this research, however, we investigate a more realistic situation in which airport gate processing time is a controllable. It is also assumed that the possible compression/expansion processing time of a flight can be continuously controlled, i.e. it can be any number in a given interval.Doing sohas some positive effectswhich lead to increasing the total performance at airports’ terminals. Depending on the situation, different objectives become important.. Therefore, a model which simultaneously (1) minimize the total cost of tardiness, earliness, delay andthe compression as well as the expansion costs of job processing time, and (2) minimize passengers overcrowding on gate is presented. In this study, we first propose a mixed-integer programming model for the formulated problem. Due to complexity of problem, two multi-objective meta-heuristic algorithms, i.e. multi-objective harmony search algorithm (MOHSA) and non-dominated sorting genetic algorithm II (NSGA-II) are applied in order to generate Pareto solutions. For calibrating the parameter of the algorithms, Taguchi method is used and three optimal levels of the algorithm’s performance are selected. The algorithms are tested with real-life data from Mehrabad International Airport for nine medium size test problems. The experimental results show that NSGA-II has better convergence near the true Pareto-optimal front as compared to MOHSA; however, MOHSA finds a better spread in the entire Pareto-optimal region.Finally, it is possible to apply some practical constraints into the model and also test them with even large real-life problems instances. تفاصيل المقالة -
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59 - Service Performance Improvement Model: The Case of Teklehaymanot General Hospital
Eshetie Berhan Selam Yibeltal Sisay GeremewIn service sector, there are challenges in keeping an optimum balance between customers' demand and availability of resources. This problem is going to be more intense in the health sector due to the fact that both arrival and service times are random. Therefore, design أکثرIn service sector, there are challenges in keeping an optimum balance between customers' demand and availability of resources. This problem is going to be more intense in the health sector due to the fact that both arrival and service times are random. Therefore, designing the service environment by keeping the optimum balance between customers’ demand and available resources is becoming a series problem in Teklehaymanot General Hospital. This paper tries to develop a model that investigates the performances of Teklehaymanot General Hospital and determines the optimum number of specialist doctors based on their respective workload. To address this objective, the study develops a model using Arena Simulation Software that considers the real working environment and scenario of Teklehaymanot General Hospital. For the purpose of this research, three years’ secondary data that include the type of services and number of specialized doctors under each service channel are collected from the hospital records and fitted to the model. The findings of the study show that there are unbalanced distributions on the daily workload among specialist doctors and extended long waiting time of patients in Teklehaymanot General Hospital. It reveals that specialist doctors who are working in pre-breast center, Hematology oncology imaging, neurology, obstetrics & gynecology, ophthalmology, pulmonology, urgent care, urology and women’s imaging are relatively overloaded, whereas those who are working in ENT Allergy Audiology, gastroenterology, Nuclear Medicine, orthopedics, physical therapy, and surgery are relatively underloaded. Moreover, from the scenario analysis, the result shows thatadditional specialized doctors in the fifteen areas are required so as to reduce the waiting time of patients by 54.41%. Therefore, the hospital is recommended to have a balanced workload distribution among specialist doctors and increase the number of specialist doctors by one or two in the fifteen service areas. تفاصيل المقالة -
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60 - The Preemptive Just-in-time Scheduling Problem in a Flow Shop Scheduling System
Javad Rezaeian Sadegh Hosseini-Kia Iraj MahdaviFlow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will أکثرFlow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs. In this paper, just-in-time (JIT) flow shop scheduling problem with preemption and machine idle time assumptions is considered in which objective function is minimizing the sum of weighted earliness and tardiness. A new non-linear mathematical model is formulated for this problem and due to high complexity of the problem meta-heuristic approaches have been applied to solve the problem for finding optimal solution. The parameters of algorithms are set by Taguchi method. Each parameter is tested in three levels. By implementation of many problems with different sizes these levels are determined .The proposed model is solved by three meta-heuristic algorithms: genetic algorithm (GA), imperialist competitive algorithm (ICA) and hybrid of GA and ICA. To evaluate the performance of the proposed algorithms many test problems have been designed. The Computational results indicate the superiority of the performance of hybrid approach than GA and ICA in finding thebest solution in reasonable computational time. تفاصيل المقالة -
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61 - Integrated Due Date Setting and Scheduling on a Single Machine Considering an Unexpected Unavailability
Mehdi Iranpoor Seyed Mohammad Taghi Fatemi GhomiIn this paper, an integrated machine scheduling withits due date setting problem has been considered. It is assumed that the machine is subject to some kind of random unavailability. Due dates should be set in an attractive and reliable manner, implying that they should أکثرIn this paper, an integrated machine scheduling withits due date setting problem has been considered. It is assumed that the machine is subject to some kind of random unavailability. Due dates should be set in an attractive and reliable manner, implying that they should be short and possible to be met. To this end, first, long due dates are penalized in the objective function. Then, for each customer order, the probability of meeting his/her promised due dateis forced to be at least as large as his/her required service level. To handle this integrated problem, first, the optimal due date formulafor any arbitrary sequence is derived. By using this formula, the mathematical programming formulation of the problem,including a nonlinear non-convex expression, is developed. By defining a piecewise linear under-estimator, the solutions of the resultantmixed integer linear programming formulation have become the lower bounds of the problem. Dynasearch is a very efficient heuristic utilizing the dynamic programming approach to search exponential neighborhoods in the polynomial time. Aniterated dynasearch heuristic is developed for the sequencing part of the problem. Each generated sequence is evaluated by computing its optimal due datesusing the above-mentioned formula. Numerical results confirmed the high quality of the solutions found by this algorithm, as compared with the lower bound. تفاصيل المقالة -
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62 - Parallel Jobs Scheduling with a Specific Due Date: Asemi-definite Relaxation-based Algorithm
Javad BehnamianThis paper considers a different version of the parallel machines scheduling problem in which the parallel jobs simultaneously requirea pre-specifiedjob-dependent number of machines when being processed.This relaxation departs from one of the classic scheduling assumpti أکثرThis paper considers a different version of the parallel machines scheduling problem in which the parallel jobs simultaneously requirea pre-specifiedjob-dependent number of machines when being processed.This relaxation departs from one of the classic scheduling assumptions. While the analytical conditions can be easily statedfor some simple models, a graph model approach is required when conflicts of processor usage are present. The main decisions and solving steps are as follows, respectively. (i) Converting the scheduling problem to graph model; (ii) Dividing jobs into independent sets: in this phase, we propose a semi-definite relaxation algorithm in which we use graph coloring concept; (iii) Sequencing the independent sets as a single-machine scheduling in which jobs in such a system arejob sets formed by using a semi-definite relaxation solution and determining the problem as a schedule that minimizes the sum of the tardiness of jobs. In this regard, after grouping the jobs by a semi-definite programming relaxation algorithm, we used the rounding algorithm for graph coloring. We also proposed a variable neighborhood search algorithm for sequencing the obtained job sets in order to minimize the sum of the tardiness. Experimental results show that this methodology is interesting by obtaining good results. تفاصيل المقالة -
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63 - Optimizing a bi-objective preemptive multi-mode resource constrained project scheduling problem: NSGA-II and MOICA algorithms
Javad Hasanpour Mohammad Ghodoosi Zahra Sadat HosseiniThe aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary wi أکثرThe aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategies. We also introduce the preemptive extension of the problem which allows activity splitting. In this paper the preemption multi-mode resource-constrained project scheduling problem (P-MMRCPSP) with Minimum makespan and the maximization of net present value (NPV) has been considered. Since the considered model is NP-Hard, The performance of our proposed model is evaluated by comparison with two well-known algorithms; non-dominated sorting genetic algorithm (NSGA II), multi-objective imperialist competitive algorithm (MOICA). These metaheuristics have been compared on the basis of a computational experiment performed on a set of instances obtained from standard test problems constructed by the ProGen project generator, where, additionally, cash flows were generated randomly with the uniform distribution. Since the effectiveness of most meta-heuristic algorithms significantly depends on choosing the proper parameters. A Taguchi experimental design method (DOE) was applied to set and estimate the proper values of GAs parameters for improving their performances. The computational results show that the proposed MOICA outperforms the NSGA-II. تفاصيل المقالة -
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64 - Machine scheduling for multitask machining
Saleh Yavari Ahmed Azab Mohammed Fazle Baki Mikel Alcelay Justin BrittMultitasking is an important part of today’s manufacturing plants. Multitask machine tools are capable of processing multiple operations at the same time by applying a different set of part and tool holding devices. Mill-turns are multitask machines with the abili أکثرMultitasking is an important part of today’s manufacturing plants. Multitask machine tools are capable of processing multiple operations at the same time by applying a different set of part and tool holding devices. Mill-turns are multitask machines with the ability to perform a variety of operations with considerable accuracy and agility. One critical factor in simultaneous machining is to create a schedule for different operations to be completed in minimum make-span. A Mixed Integer Linear Programming (MILP) model is developed to address the machine scheduling problem. The adopted assumptions are more realistic when compared with the previous models. The model allows for processing multiple operations simultaneously on a single part; parts are being processed on the same setup and multiple turrets can process a single operation of a single job simultaneously performing multiple depths of cut. A Simulated Annealing algorithm with a novel initial solution and assignment approach is developed to solve large instances of the problem. تفاصيل المقالة -
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65 - Nurse Scheduling Problem by Considering Fuzzy Modeling Approach to Treat Uncertainty on Nurses’ Preferences for Working Shifts and Weekends off
Hamed Jafari Hassan HalehNowadays, the nurse scheduling problem (NSP) has attracted a great amount of attentions. In this problem,the nurses are scheduled to be assigned to the shifts by considering the required nurses for each day during the planning horizon. In the current study, a bi-objecti أکثرNowadays, the nurse scheduling problem (NSP) has attracted a great amount of attentions. In this problem,the nurses are scheduled to be assigned to the shifts by considering the required nurses for each day during the planning horizon. In the current study, a bi-objective mathematical model is formulated in order to maximize the preferences of the nurses to work on the shifts in addition to be off on the weekends. In real-world problems, higher quality schedules are provided considering the uncertainty. In this point of view, we investigate the uncertainty on the preferences of the nurses for the working shifts and the weekends off. In fact, a compensatory fuzzy approach based on the Werners’ fuzzy and operator is proposed to investigate the effects of the uncertainty on the considered research problem. Then, several sample problems are generated to support the efficiency of the developed fuzzy model. Finally, a sensitivity analysis is implemented to determine the effects of the changes of the parameters on the obtained results. تفاصيل المقالة -
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66 - Minimizing the operational costs in a flexible flow shop scheduling problem with unrelated parallel machines
Ali Hassani Seyed Mohamad Hasan Hosseini Foroogh BehrooziThis paper investigates a flexible flow shop scheduling problem with the aim of minimizing the operational costs as a new objective function. In this production system, there are some unrelated parallel machines with different performances and different technology level أکثرThis paper investigates a flexible flow shop scheduling problem with the aim of minimizing the operational costs as a new objective function. In this production system, there are some unrelated parallel machines with different performances and different technology levels in the first stage and each other stage consists of a single machine. Setup times are assumed as sequence-dependent and are need when a machine starts to process a new job. Some of the parallel machines in the first stage are multifunctional and can do several processes on jobs. So, the jobs that are assigned to these machines do not need to be processed in some next stages. This problem is described with an example, and its parameters and decision variables are defined. Then a mathematical model based on mixed-integer linear programming (MIP) is developed to solve the problem in small-sized scales. As this problem is discussed in an Np-hard environment, the Genetic Algorithm (GA) is applied to solve the considered problem on practical-sized scales. Due to the result, the operational costs conflict with makespan as a common objective function in scheduling problems. Therefore, the supplementary analysis has been presented considering a restriction on the makespan. تفاصيل المقالة -
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67 - Scheduling on flexible flow shop with cost-related objective function considering outsourcing options
Mojtaba Enayati Ebrahim Asadi-Gangraj Mohammad Mahdi PaydarThis study considers outsourcing decisions in a flexible flow shop scheduling problem, in which each job can be processed by either an in-house production line or outsourced. The selected objective function aims to minimize the weighted sum of tardiness costs, in-house أکثرThis study considers outsourcing decisions in a flexible flow shop scheduling problem, in which each job can be processed by either an in-house production line or outsourced. The selected objective function aims to minimize the weighted sum of tardiness costs, in-house production costs, and outsourcing costs with respect to the jobs due date. The purpose of the problem is to select the jobs that must be processed in-house, schedule processing of the jobs in-house, and finally select and assign other jobs to the subcontractors. We develop a mixed-integer linear programming (MILP) model for the research problem. Regarding the complexity of the research problem, the MILP model cannot be used for large-scale problems. Therefore, four metaheuristic algorithms, including SA, GA, PSO, hybrid PSO-SA, are proposed to solve the problem. Furthermore, some random test problems with different sizes are generated to evaluate the effectiveness of the proposed MILP model and solution approaches. The obtained results demonstrate that the GA can obtain better solutions in comparison to the other algorithms. تفاصيل المقالة -
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68 - An Integrated Bi-Objective Mathematical Model for Minimizing Take-off Delay and Passenger Dissatisfaction
Razieh Larizadeh Reza RamezanianAs air transportation has increased in recent years, it is necessary for airport planners to optimally manage aircraft ground traffic on stands, taxiways and runways in order to minimize flight delay and passenger dissatisfaction. A closer look at the literature in this أکثرAs air transportation has increased in recent years, it is necessary for airport planners to optimally manage aircraft ground traffic on stands, taxiways and runways in order to minimize flight delay and passenger dissatisfaction. A closer look at the literature in this area indicates that most studies have merely focused on one of these resources which in a macroscopic level may result in aircrafts’ collision and ground traffic at the airport. In this paper, a new bi-objective Mixed-Integer Linear Programming (MILP) model is developed to help airport management to integrate Gate Assignment Problem (GAP) and Runway Scheduling Problem (RSP) considering taxiing operation for departing flights. The proposed model aims to help airport planners to 1) minimize any deviation from preferred schedule and 2) minimize transit passengers’ walking distance. Due to the complexity of the research problem, a Normalized Weighted Sum Method (NWSM) is applied to solve small-sized problems and two meta-heuristics, namely NSGA-II and MOGWO, are used for large-scale instances to generate Pareto optimal solutions. The performance of these algorithms is assessed by well-known coverage and convergence measures. Based on the most criteria, the results indicate that MOGWO outperforms NSGA-II. تفاصيل المقالة -
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69 - A bi-objective mathematical model for the patient appointment scheduling problem in outpatient chemotherapy clinics using Fuzzy C-means clustering: A case study
Masoud Rabbani Alireza Khani amirreza Zare niloofar Akbarian-SaraviIn healthcare, the Patient Appointment Scheduling (PAS) problem is one of the critical issues in Outpatient Chemotherapy Clinics (OCC). In the wake of this, this paper proposes a novel bi-objective mathematical programming model for solving the PAS problem in OCC. The d أکثرIn healthcare, the Patient Appointment Scheduling (PAS) problem is one of the critical issues in Outpatient Chemotherapy Clinics (OCC). In the wake of this, this paper proposes a novel bi-objective mathematical programming model for solving the PAS problem in OCC. The developed mathematical model is inspired by cellular manufacturing. The first objective function minimizes the completion time of all treatments, and the second objective function maximizes the use of nurses' skills while considering clustered patients about their characteristics. To solve the bi-objective mathematical model, for the first time a hybrid approach based on Torabi-Hassini (TH) and Lagrange method is utilized. The results indicate that an increase in the number of nurses will enhance the treatment completion speed and allocation of nurses’ work skill. On the other hand, an increase in the number of chairs in clinics will decrease the assignments of nurses’ skills priority. The study supports decision makers in considering nurses' skills for the PAS problem. The results also denote the desirability of the proposed model. To validate the proposed model, OCC in Tehran is considered as a case study. Computational results reveal that considering nurses' skills in OCC and using the fuzzy clustering model, as a new method in patient clustering, lead to achieving a desirable and more realistic outcome. تفاصيل المقالة -
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70 - Two-Machine Open Shop Scheduling with Proportionally Deteriorating Jobs and Makespan Objective
Ching-Fang LiawThis manuscript examines the two-machine open shop scheduling problem where the latter a job is scheduled the longer it takes to process this job. The performance is measured by minimizing the makespan. By modifying existing algorithms for the corresponding problem with أکثرThis manuscript examines the two-machine open shop scheduling problem where the latter a job is scheduled the longer it takes to process this job. The performance is measured by minimizing the makespan. By modifying existing algorithms for the corresponding problem with fixed processing times, two new algorithms are developed for the problem under consideration. The proofs of optimality of both algorithms are presented. The execution of these algorithms is illustrated by two numerical examples. Finally, both algorithms are further modified to solve a more generalized problem where the time demanded to process a job is a general linear function of its beginning time. تفاصيل المقالة -
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71 - A mathematical programming model for single round-robin tournament problem: A case study of Volleyball Nations League
Hamed Jafari Morteza RajabzadehIn this study, a mathematical programming model is developed for a single round-robin tournament problem to provide a schedule for the preliminary round of the Volleyball Nations League. In this setting, the aim is to assign the teams to the pools at each week as well a أکثرIn this study, a mathematical programming model is developed for a single round-robin tournament problem to provide a schedule for the preliminary round of the Volleyball Nations League. In this setting, the aim is to assign the teams to the pools at each week as well as to specify the host teams of the pools. This schedule is obtained by minimizing the sum of the differences between the total distance traveled by every team and the average of the total distances traveled by all teams. Then, to evaluate the performance of the developed model, it is applied to obtain the optimal schedule for the preliminary round of the Volleyball Men’s Nations League in year 2018. The results indicate that the sum of the travel distance deviations from the average of the total travel distances of all teams obtained from the schedule provided by the mathematical model is significantly lower than that calculated from the schedule presented by the International Volleyball Federation. Moreover, the schedule presented by the International Volleyball Federation leads to a percentage gap of 449.92% in comparison with the optimal schedule provided by the developed model. تفاصيل المقالة -
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72 - Developing and solving the multi-objective flexible and sustainable job shop scheduling problem with reverse flow and job rotation considerations in uncertain situations
Arsalan Shojaei Davood Jafari Mehran Khalag Parshang DokohakiFlexible job shop scheduling problem (FJSP) has received a lot of attention in recent years, but the important point is that this field of study can be subject to many assumptions and lots of innovations can be considered. One of these can be reverse flow, which has bee أکثرFlexible job shop scheduling problem (FJSP) has received a lot of attention in recent years, but the important point is that this field of study can be subject to many assumptions and lots of innovations can be considered. One of these can be reverse flow, which has been overlooked in many studies, while its effect on the cost and time of construction is undeniable. Other areas such as job rotation as well as issues related to sustainability can be of particular importance in this area and have not been reviewed in previous researches. Therefore, the present study seeks to provide a model to optimize the multi-objective flexible job shop scheduling problem concerning the issues of sustainability with reverse flow and job rotation considerations. For this purpose, a multi-objective mathematical scheduling model is developed, the first goal of which is to minimize the construction time and the second goal is to minimize the issues related to sustainability. To solve the model, two methods were used: Sensitivity analysis and meta-heuristic. The whale optimization algorithm (WOA) was employed in the meta-heuristic method. The results of the implementation of WOA indicate the efficiency of the proposed algorithm, while the findings of the sensitivity analysis also point to the effect of research innovations on the objective functions of the problem. تفاصيل المقالة -
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73 - An Efficient Extension of Network Simplex Algorithm
Hassan Rashidi Edward P.K TsangIn this paper, an efficient extension of network simplex algorithm is presented. In static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of أکثرIn this paper, an efficient extension of network simplex algorithm is presented. In static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by Network Simplex Algorithm (NSA) and NSA+, which extended the standard NSA. The algorithms are based on graph model and their performances are at least 100 times faster than traditional simplex algorithm for Linear Programs. Many random data are generated and fed to the model for 50 vehicles. We compared results of NSA and NSA+ for the static automated vehicle scheduling problem. The results show that NSA+ is significantly more efficient than NSA. It is found that, in practice, NSA and NSA+ take polynomial time to solve problems in this application. تفاصيل المقالة -
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74 - Scheduling in Container Terminals using NetworkSimplex Algorithm
Hassan RashidiIn static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by the Network Simplex أکثرIn static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by the Network Simplex Algorithm (NSA). The algorithm is based on graph model and their performances are at least 100 times faster than traditional simplex algorithm for Linear Programs. Many random data are generated and fed to the model for 50 vehicles. The results show that NSA is fast and efficient. It is found that, in practice, NSA takes polynomial time to solve problems in this application. تفاصيل المقالة -
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75 - A Bi-objective Pre-emption Multi-mode Resource Constrained Project Scheduling Problem with due Dates in the Activities
zahra Sadat Hosseini Javad Hassan pour Emad RoghanianIn this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. Although optimization of bi-objective problems with due dates أکثرIn this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. Although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the P-MMRCPSP while due dates are included in the activities. This paper tries to bridge this gap by studying tardiness MMRCPSP, in which the objective is to minimize total weighted tardiness and to maximize the net present value (NPV). In order to solve the given problem, we introduced a Non-dominated Ranking Genetic Algorithm (NRGA) and Non-Dominated Sort Genetic Algorithm (NSGA-II). Since the effectiveness of most meta-heuristic algorithms significantly depends on choosing the proper parameters. A Taguchi experimental design method was applied to set and estimate the proper values of GAs parameters for improving their performances. To prove the efficiency of our proposed meta-heuristic algorithms, a number of test problems taken from the project scheduling problem library (PSPLIB) were solved. The computational results show that the proposed NSGA-II outperforms the NRGA. تفاصيل المقالة -
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76 - A Simulated Annealing Algorithm for Multi Objective Flexible Job Shop Scheduling with Overlapping in Operations
Mehrzad Abdi Khalife Babak Abbasi Amirhossein Kamali Dolat abadiIn this paper, we considered solving approaches to flexible job shop problems. Makespan is not a good evaluation criterion with overlapping in operations assumption. Accordingly, in addition to makespan, we used total machine work loading time and critical machine work أکثرIn this paper, we considered solving approaches to flexible job shop problems. Makespan is not a good evaluation criterion with overlapping in operations assumption. Accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. As overlapping in operations is a practical assumption in chemical, petrochemical, and glass industries, we used simulated annealing algorithm for multi-objective flexible job shop scheduling problem with overlapping in operations to find a suitable solution. To evaluate performance of the algorithm, we developed a mixed integer linear programming model, and solved it with the classical method (branch and bound). The results showed that in small size problems, the solutions of the proposed algorithm and the mathematical model were so close, and in medium size problems, they only had lower and upper bounds of solution and our proposed algorithm had a suitable solution. We used an experimental design for improving the proposed algorithm. تفاصيل المقالة -
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77 - Meta heuristic for Minimizing Makespan in a Flow-line Manufacturing Cell with Sequence Dependent Family Setup Times
Behzad Nikjo Javad RezaeianThis paper presents a new mathematical model for the problem of scheduling part families and jobs within each part family in a flow line manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the maximum completion أکثرThis paper presents a new mathematical model for the problem of scheduling part families and jobs within each part family in a flow line manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the maximum completion time of the last job on the last machine (makespan) while processing parts (jobs) in each family together. Gaining an optimal solution for this type of complex problem in large sizes in reasonable computational time using traditional approaches or optimization tools is extremely difficult. A meta-heuristic method based on Simulated Annealing (SA) is proposed to solve the presented model. Based on the computational analyses, the proposed algorithm was found efficient and effective at finding good quality solutions. تفاصيل المقالة -
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78 - A New Approach in Job Shop Scheduling: Overlapping Operation
parviz Fattahi mohammad Saidi MehrabadIn this paper, a new approach to overlapping operations in job shop scheduling is presented. In many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. In each job, أکثرIn this paper, a new approach to overlapping operations in job shop scheduling is presented. In many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. In each job, embedded operations can be performed due to overlapping considerations in which each operation may be overlapped with the others because of its nature. The effects of the new approach on job shop scheduling problems are evaluated. Since the problem is well known as NP-Hard class, a simulated annealing algorithm is developed to solve large scale problems. Moreover, a mixed integer linear programming (MILP) method is applied to validate the proposed algorithm. The approach is tested on a set of random data to evaluate and study the behavior of the proposed algorithm. Computational experiments confirmed superiority of the proposed approach. To evaluate the effect of overlapping considerations on the job shop scheduling problem, the results of classical job shop scheduling with the new approach (job shop scheduling problem with overlapping operations) are compared. It is concluded that the proposed approach can improve the criteria and machines utilization measures in job shop scheduling. The proposed approach can be applied easily in real factory conditions and for large size problems. It should thus be useful to both practitioners and researchers. تفاصيل المقالة -
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79 - Multi-objective and Scalable Heuristic Algorithm for Workflow Task Scheduling in Utility Grids
Vahid Kahejvand Hossein Pedram Mostafa ZandiehTo use services transparently in a distributed environment, the Utility Grids develop a cyber-infrastructure. The parameters of the Quality of Service such as the allocation-cost and makespan have to be dealt with in order to schedule workflow application tasks in the U أکثرTo use services transparently in a distributed environment, the Utility Grids develop a cyber-infrastructure. The parameters of the Quality of Service such as the allocation-cost and makespan have to be dealt with in order to schedule workflow application tasks in the Utility Grids. Optimization of both target parameters above is a challenge in a distributed environment and may conflict one another. We, therefore, present a novel heuristic algorithm for scheduling a workflow application on Utility Grids. Our proposed algorithm optimizes the allocation-cost and makespan in a scalable and very low runtime. The results of the wide-spread simulation indicate that the proposed algorithm is scalable against an increase in the application size and task parallelism of the application. The proposed algorithm effectively outperforms the current algorithms in terms of the allocation-cost, makespan and runtime scalability. تفاصيل المقالة -
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80 - An Iterated Greedy Algorithm for Flexible Flow Lines with SequenceDependent Setup Times to Minimize Total Weighted Completion Time
Bahman Naderi mostafa Zandieh Seyed Mohammad Taghi Fatemi GhomiThis paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is con أکثرThis paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of IGA are compared against those of some other existing algorithms. The effectiveness of IGA is demonstrated through comparison. تفاصيل المقالة -
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81 - The preemptive resource-constrained project scheduling problem subjectto due dates and preemption penalties: An integer programming approach
Behrouz Afshar nadjafi Shahram ShadrokhExtensive research has been devoted to resource constrained project scheduling problem. However, little attention has been paid to problems where a certain time penalty must be incurred if activity preemption is allowed. In this paper, we consider the project scheduling أکثرExtensive research has been devoted to resource constrained project scheduling problem. However, little attention has been paid to problems where a certain time penalty must be incurred if activity preemption is allowed. In this paper, we consider the project scheduling problem of minimizing the total cost subject to resource constraints, earliness-tardiness penalties and preemption penalties, where each time an activity is started after being preempted; a constant setup penalty is incurred. We propose a solution method based on a pure integer formulation for the problem. Finally, some test problems are solved with LINGO version 8 and computational results are reported. تفاصيل المقالة -
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82 - A Mathematical Model for a Flow Shop Scheduling Problem withFuzzy Processing Times
Jafar Razmi Reza Tavakoli moghaddam Mohammad SaffariThis paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical obje أکثرThis paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable makespan and the probability of minimizing the makespan. These criteria can be considered for fuzzy problems as well. In this paper, we propose a solution for the fuzzy model by the use of fuzzy logic based on developing the model presented by MacCahon [18]. تفاصيل المقالة -
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83 - Exact Mixed Integer Programming for Integrated Scheduling and Process Planning in Flexible Environment
Mohammad Saidi Mehrabad Saeed ZarghamiThis paper presented a mixed integer programming for integrated scheduling and process planning. The presented process plan included some orders with precedence relations similar to Multiple Traveling Salesman Problem (MTSP), which was categorized as an NP-hard problem. أکثرThis paper presented a mixed integer programming for integrated scheduling and process planning. The presented process plan included some orders with precedence relations similar to Multiple Traveling Salesman Problem (MTSP), which was categorized as an NP-hard problem. These types of problems are also called advanced planning because of simultaneously determining the appropriate sequence and minimizing makespan in the process of scheduling. There are alternative machines for each operation and different sequences for each order, which create a flexible environment for production planning. In process planning ansd integrated scheduling, most mathematical models have two sets of ordered pairs with precedence or non-precedence relations between operations; therefore, these models cannot be solved using optimization software. Therefore, in this paper, this problem was modeled by a new approach and solved by GAMS software. The model was validated by the existing data in the literature. تفاصيل المقالة -
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84 - An Exact Algorithm for the Mode Identity Project Scheduling Problem
Behrouz Afshar Nadjafi Amir Rahimi Hamid KarimiIn this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (MRCPSP) withmode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to bep أکثرIn this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (MRCPSP) withmode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to beprocessed in the same mode. We present a depth-first branch and bound algorithm for the resource constrained project scheduling problemwith mode identity. The proposed algorithm is extended with some bounding rules to reduce the size of branch and bound tree. Finally,some test problems are solved and their computational results are reported. تفاصيل المقالة -
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85 - A Multi-Mode Resource-Constrained Optimization of Time-Cost Trade-off Problems in Project Scheduling Using a Genetic Algorithm
Sedigheh Nader Abadi Emad Roghanian Hadi AghassiIn this paper, we present a genetic algorithm (GA) for optimization of a multi-mode resource constrained time cost trade off (MRCTCT) problem. The proposed GA, each activity has several operational modes and each mode identifies a possible executive time and cost of the أکثرIn this paper, we present a genetic algorithm (GA) for optimization of a multi-mode resource constrained time cost trade off (MRCTCT) problem. The proposed GA, each activity has several operational modes and each mode identifies a possible executive time and cost of the activity. Beyond earlier studies on time-cost trade-off problem, in MRCTCT problem, resource requirements of each execution mode are also allocated and the highest quantities of these resources are limited. In the MRCTCT, the goal is to reduce the total project cost with respect to the resource restrictions .The gene value is encoded as the mode index which is selected from among modes of the activity randomly. For indicating construction mode of the activity, integer encoding is applied instead of binary encoding. Additionally, the selection of genes for mutation is based on chromosome value, as solution convergence rate is high. The crossover operator of GA is based on a two-point method. This paper also offers a multi-attribute fitness function for the problem. This function can vary by decision maker (DM) preferences (time or cost). In this paper, a two-phase algorithm is proposed in which both the effects of time-cost trade-off and resource-constrained allocation are taken into account. A GA-based time-cost trade-off analysis is improved for choosing the execution mode of every activity through the trade-off of time and cost, followed by proposing a resource constrained allocation algorithm to generate an optimum schedule without overriding the project constraints. Lastly, the model is verified by means of a case study and a real project. تفاصيل المقالة -
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86 - A Memetic Algorithm for Hybrid Flowshops with Flexible MachineAvailability Constraints
Fariborz Jolai mostafa zandieh Bahman NaderiThis paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed أکثرThis paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed or/and conservative policies, we explore a case in which PM activities might be postponed or expedited while necessary. Regarding this flexibility in PM activities, we expect to obtain more efficient schedule. A simple technique is employed to schedule production jobs along with the flexible MACs caused by PM. To solve the problem, we present a high performing metaheuristic based on memetic algorithm incorporating some advanced features. To evaluate the proposed algorithm, the paper compares the proposed algorithm with several wellknown algorithms taken from the literature. Finally, we conclude that the proposed algorithm outperforms other algorithms. تفاصيل المقالة -
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87 - Modelling and Scheduling Lot Streaming Flexible Flow Lines
Bahman naderi Mehdi YazdaniAlthough lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematic أکثرAlthough lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreover, a novel artificial bee colony optimization is developed. This algorithm utilizes five effective mechanisms to solve the problem. To evaluate the algorithm, it is compared with adaptation of four available algorithms. The statistical analyses showed that the proposed algorithm significantly outperformed the other tested algorithms. تفاصيل المقالة -
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88 - Fuzzy Programming for Parallel Machines Scheduling: Minimizing Weighted Tardiness/Earliness and Flow Time through Genetic Algorithm
Mohammad Asghari Samaneh NezhadaliAppropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is j أکثرAppropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for appraising a multi-objective programing that minimize total weighted tardiness, earliness and total flowtime with fuzzy parameters on parallel machines, simultaneously with respect to the impact of machine deterioration. Besides, in this paper attempted to present a defuzzification approach and a heuristic method based on genetic algorithm (GA) to solve the proposed model. Finally, several dominant properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver and the simulated annealing method that is followed by illustrating some instances for indicating validity and efficiency of the method. تفاصيل المقالة -
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89 - توسعه مدل ریاضی چند هدفه برای زمان بندی پروژه با در نظر گرفتن شیوه های مختلف اجرای فعالیت ها و اثرات زیست محیطی و حل آن به روش اپسیلون توسعه یافته
حسینعلی حیدری هیرش سلطان پناه هیوا فاروقی ایوب رحیم زادهامروزه دغدغه های مدیران در پروژه های نفت،گاز و پتروشیمی،تکمیل پروژه ها در موعد مقرر با بالاترین سطح کیفیت اجرای فعالیت ها، صرف کمترین هزینه های مالی و کمترین اثرات مخرب زیست محیطی می باشد. از این رو برقراری موازنه بین چهار هدف متضاد زمان، هزینه،کیفیت و اثرات زیست محیطی أکثرامروزه دغدغه های مدیران در پروژه های نفت،گاز و پتروشیمی،تکمیل پروژه ها در موعد مقرر با بالاترین سطح کیفیت اجرای فعالیت ها، صرف کمترین هزینه های مالی و کمترین اثرات مخرب زیست محیطی می باشد. از این رو برقراری موازنه بین چهار هدف متضاد زمان، هزینه،کیفیت و اثرات زیست محیطی از اهمیت ویژه ای برای مدیران برخوردار است. با نگاهی عمیق تر به اهداف مذکور مشخص می شود تمرکز بر روی هر کدام از اهداف چهارگانه منجر به ایجاد تغییراتی بر روی سایر اهداف خواهد شد به عبارتی دیگر بین اهداف مذکور تناقض وجود دارد. به همین منظور در این مطالعه سعی شده است مدلی ریاضی برای موازنه اهداف چهارگانه ارائه گردد که خواسته ها و نیازهای مدیران پروژه را برآورد سازد و به مسائل دنیای واقعی نزدیکتر باشد. مدل ارائه شده از نوع مدل ریاضی چند هدفه صفر و یک است که در این مدل فعالیت های پروژه دارای ماهیتی چند حالته و غیرقابل انقطاع هستند و ظرفیت منابع محدود و مشخص و روابط پیش‌نیازی فعالیت ها از نوع روابط پیش‌نیازی کلی در نظر گرفته شده است. جهت اعتبارسنجی، مدل پیشنهادی با استفاده از نرم افزار GAMS و حل کننده CPLEX توسط روش محدودیت اپسیلون توسعه یافته بر روی داده های واقعی یک پروژه نفتی حل شده و جواب بهینه آن به دست آمده است و نتایج حاصل از تحلیل حساسیت های مختلف گزارش شده است. تفاصيل المقالة -
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90 - Provide a model for manpower scheduling using a hybrid meta-innovative algorithm in the Water and Sewerage Company
seyed ahmad shayan nia roghayeh mirataollahi olyaOne of the biggest challenges of projects is the limitation in human resources and, more clearly, the limitation in the number of skilled workers. Proper allocation of workers can increase the quality of production. Production workers, as the largest producer of the pro أکثرOne of the biggest challenges of projects is the limitation in human resources and, more clearly, the limitation in the number of skilled workers. Proper allocation of workers can increase the quality of production. Production workers, as the largest producer of the production leap, play a key role in improving the country's production system. Therefore, their proper timing is very important. In this research, by developing the concept of fatigue caused by the same work into two types of positive and negative fatigue caused by doing similar work and not just the same, a new and flexible model is presented that uses it Tasks can be scheduled so that similar tasks are assigned to each operator in the smallest programmable period and dissimilar tasks in the largest programmable period, so that the total allocation cost (including the total cost of doing the work and the total cost of fatigue). Because the proposed workflow scheduling model is formulated as a multi-period BoH allocation model and formulated as a nonlinear integer model, it falls into the category of compositional optimization. To overcome its algorithmic complexity, the Simulated Anealing algorithm is developed. تفاصيل المقالة -
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91 - Presenting a super-heuristic genetic algorithm for investment in project resource
nooshin hafezi zadehDeveloping a suitable plan and optimal use of available facilities are considered important factors in today's competitive world. The aim of this research is to provide an innovative genetic algorithm for the problem of investment in project resources. In terms of the p أکثرDeveloping a suitable plan and optimal use of available facilities are considered important factors in today's competitive world. The aim of this research is to provide an innovative genetic algorithm for the problem of investment in project resources. In terms of the purpose, this research is an applied and, in terms of data collection, it is of a mathematical analytical type. According to the positive experiences of using genetic algorithm to solve the problems of the specification in limited resources, this research aims to create two genetic algorithms for a type of allocation problem called investment problem in resources. Genetic algorithm designed was tested on the problems investigated by Mohring representing that the above problems are not complicated enough, because genetic algorithm has obtained optimal solution for the problems rapidly. So, more problems were generated by Progen software through more tests, and, in general, more than 15,000 problems tested by genetic algorithm. Then, by making changes in the above algorithm and using Akpan method and modifying this method, genetic algorithm has been improved. The method developed has also been compared with the previous method during the tests. After setting the parameters on 20 activity problems, the tests were conducted on 10 and 14 activity problems. It represented that new algorithm works more efficiently on these problems. On 30 activity problems in Dergzel and Kims, new and previous genetic algorithms were compared by using multivariate variance analysis and Duncan's test indicating a significant improvement in the answers. تفاصيل المقالة -
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92 - Developing a Technique Based on Extended Gravitational Force to Solve Scheduling Problem
عزیز نوروزی نودهی عباس طلوعی اشلقیScheduling is to determine the priorities or arrange the activities to meet the needs, limitations and certain goals. Because the time is always a limited resource, all activities should be scheduled to use optimally and certainly the resource. Gravitational force alg أکثرScheduling is to determine the priorities or arrange the activities to meet the needs, limitations and certain goals. Because the time is always a limited resource, all activities should be scheduled to use optimally and certainly the resource. Gravitational force algorithm, like other evolutionary algorithms, is inspired by nature. The effect of the gravity on the objects reciprocally and to all objects in the space is the main idea of this algorithm. In this study, after reviewing the literature, a problem of timetable scheduling for academic courses will be studied and then analyzed by using the proposed algorithm based on the principles of gravitational force algorithm. In this algorithm, the gravitational force between the answers can be calculated through 2 methods. Firstly, an answer will be selected from the local neighborhood of the current answer and the gravitational force between these two answers will be calculated. Secondly, the gravitational force between all neighbor answers are calculated in the neighborhood of the current answer but not limited to one neighbor answer. By comparing the methods, the result is that the first method has a relative superiority in terms of the parameters of speed and quality. تفاصيل المقالة -
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93 - Multi-Objective Optimization for Coverage Aware Sensor Node Scheduling in Directional Sensor Networks
Nemat Mottaki Homayun Motameni Hosein MohamadiThe directional sensor networks (DSNs) are mainly focused to prolong the network lifetime and to optimize the energy consumption of sensors. The number of sensors deployed in an environment is much higher than those required for providing the coverage; therefore, the en أکثرThe directional sensor networks (DSNs) are mainly focused to prolong the network lifetime and to optimize the energy consumption of sensors. The number of sensors deployed in an environment is much higher than those required for providing the coverage; therefore, the energy-aware methods are needed to select the sensors. Coverage is considered a major problem in DSNs and is a criterion for quality of service (QOS).In this regard, the sensor scheduling method has been discussed by researchers to prolong the sensor lifetime in a network. The present paper proposes an NSGAII-based algorithm to solve the sensors 'scheduling. This paper aimed at finding a practical solution in solving the multi-objective problems by using the multi-objective evolutionary algorithm method. There are two parameters presented for evaluating the solutions, including the number of sensors, the target coverage. To confirm the high performance of the proposed algorithm, it was compared with the recently presented algorithm. According to the simulation findings, the algorithm had better results in the comparison parameters. تفاصيل المقالة -
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94 - Solving Group Scheduling Problem in No-wait Flow Shop with Sequence Dependent Setup Times
Abolfazl Adressi Reza Bashirzadeh Vahid Azizi Saeed Tasouji HassanpourDifferent manufacturing enterprises use regularly scheduling algorithms in order to help meeting demands over time and reducing operational costs. Nowadays, for a better useofresources and manufacturingin accordance withcustomer needs and given the level ofcompetitionbe أکثرDifferent manufacturing enterprises use regularly scheduling algorithms in order to help meeting demands over time and reducing operational costs. Nowadays, for a better useofresources and manufacturingin accordance withcustomer needs and given the level ofcompetitionbetweencompanies, employing asuitablescheduling programhasa double importance. Conventional productionmethods are constantly substituted with new ones for improving the efficiency and effectiveness of the entire production system. In this paper, two Meta-heuristic algorithms, Genetic and simulated annealing, have been used in order to solve the group scheduling problem of jobs in a single stage No-wait flow shop environment in which setup times are sequence dependent,. The purpose of solving the proposed problem is to minimize the maximum time needed to complete the jobs (Makespan). The results show that Genetic algorithm is efficient in problems with small and large dimensions, with respect to time parameter of problem solving. تفاصيل المقالة -
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95 - Solving the Problem of Scheduling Unrelated Parallel Machines with Limited Access to Jobs
Mohammadreza Naghibi Abolfazl AdressiNowadays, by successful application of on time production concept in other concepts like production management and storage, the need to complete the processing of jobs in their delivery time is considered a key issue in industrial environments. Unrelated parallel machin أکثرNowadays, by successful application of on time production concept in other concepts like production management and storage, the need to complete the processing of jobs in their delivery time is considered a key issue in industrial environments. Unrelated parallel machines scheduling is a general mood of classic problems of parallel machines. In some of the applications of unrelated parallel machines scheduling, when machines have different technological levels and are not necessarily able to process each one of the existing jobs in the group of jobs and in many of the industrial environments, a sequence dependent setup time takes place during exchanging jobs on the machines. In this research, the unrelated parallel machines scheduling problem has been studied considering the limitations of sequence dependent setup time of processing of jobs and limited accessibility to machines and jobs with the purpose of minimizing the total weighting lateness and earliness times. An integer scheduling model is proposed for this problem. Also, a meta-heuristically combined method consisting of Genetic algorithm and Particle swarm optimization (PSO) algorithm for its solutions is proposed. The obtained results of the proposed algorithm show that the proposed algorithm is very efficient especially in problems with large dimensions. تفاصيل المقالة -
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96 - Scheduling Problem of Virtual Cellular Manufacturing Systems (VCMS); Using Simulated Annealing and Genetic Algorithm based Heuristics
Saeed Taouji Hassanpour Reza Bashirzadeh Abolfazl Adressi Behnam BahmankhahIn this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufactur أکثرIn this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufacturing of a part family. Although this grouping is not reflected in the physical structure of the manufacturing system, but machines are spread on the shop floor physically. In this paper, there are multiple jobs with different manufacturing processing routes. First, we develop the mathematical model for the problem, and then we present the suggested algorithms. The scheduling objective is weighed tardiness and total travelling distance minimization. The problem is divided into two branches: small scale and large scale. For small scale, the results of GA and SA are compared to GAMS. For large scale problems, due to the time limitation of 3600 seconds, the results of GA and SA are compared to each other. Computational results show that both SA ad GA algorithms perform properly but SA is likely to turn out well in finding better solutions in shorter times especially in large scale problems. تفاصيل المقالة -
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97 - ارائه یک الگوریتم جدید برای زمانبندی پیوند شبکه‌های توری بی‌سیم چند ورودی-چند خروجی با تداخل متفاوت بر مبنای کلونی مورچگان
صادق زرمهی سید محمود دانشور فرزانگان آوید آوخاگر چه شبکه‌های بی‌سیم نسل جدید از نظر هزینه‌ی نصب و توسعه، فن‌آوری مناسبی برای زیرساخت اینترنت محسوب می‌شوند، ولی به دلیل محدودیت در ظرفیت و مقیاس پذیری، چالش‌های زیادی را مانند زمانبندی پیوند و مسیریابی به دنبال دارند. در این مقاله، با تمرکز بر روش دسترسی چندگانه أکثراگر چه شبکه‌های بی‌سیم نسل جدید از نظر هزینه‌ی نصب و توسعه، فن‌آوری مناسبی برای زیرساخت اینترنت محسوب می‌شوند، ولی به دلیل محدودیت در ظرفیت و مقیاس پذیری، چالش‌های زیادی را مانند زمانبندی پیوند و مسیریابی به دنبال دارند. در این مقاله، با تمرکز بر روش دسترسی چندگانه تقسیم زمانی الگوریتم جدیدی با عنوان کلونی مورچه ها برای زمانبندی پیوند در شبکه های مش (ALSM) بر مبنای رنگ آمیزی گراف و الگوریتم کلونی مورچگان ارائه شده که با زمانبندی پیوندها امکان تصادم را به صفر می‌رساند. در این الگوریتم سعی خواهد شد اندازه ابرقاب‌ها و اختصاص هر پیوند به یک شکاف زمانی به گونه‌ای باشد که با توجه به محدودیت تداخل پیوندها و نیز درجه آزادی آنتن‌های مورد استفاده برای ارسال یا دریافت، تأخیر انتها به انتها کاهش و ظرفیت شبکه افزایش یابد. در شبکه‌های توری بی‌سیم چند ورودی-چند خروجی دو نوع تداخل (تداخل ضعیف و قوی) وجود دارد. در ALSM، الگوریتم کلونی مورچگان به گونه‌ای اصلاح شده که بتوان با در نظر گرفتن این دو نوع تداخل، زمانبندی بهینه پیوندها را به دست آورد. نتایج این تحقیق نشان میدهد که الگوریتم ALSM در مقایسه با الگوریتم‌های دیگری که در سالهای اخیر ارائه شده است با طول ابرفریم کوتاه‌تری می‌تواند زمانبندی پیوندها را انجام دهد. تفاصيل المقالة -
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98 - یک چارچوب غیرمتمرکز مبتنی بر تبادل های انرژی رخ‌به‌رخ در ریزشبکهها برای بهبود تاب‌آوری با درنظرگرفتن استقلال و حریم خصوصی
محمد دوستی زاده حسن جلیلی عباس باباییبروز حوادث شدیدی مانند رخداد سیل، زلزله و طوفان سبب ایجاد اختلال در عملکرد شبکه های توزیع شده و جزیره ای شدن آن ها را به دنبال دارد. در این شرایط، در صورتی که شبکه های توزیع دارای ریزشبکه ها باشند، این ریزشبکه ها قادرند تا با کمک زیرساخت های فنی و ارتباطی خود از أکثربروز حوادث شدیدی مانند رخداد سیل، زلزله و طوفان سبب ایجاد اختلال در عملکرد شبکه های توزیع شده و جزیره ای شدن آن ها را به دنبال دارد. در این شرایط، در صورتی که شبکه های توزیع دارای ریزشبکه ها باشند، این ریزشبکه ها قادرند تا با کمک زیرساخت های فنی و ارتباطی خود از شبکه اصلی جدا شده و با اتصال به یکدیگر به تبادل انرژی پرداخته و هزینه های بهره برداری و خاموشی خود را کاهش دهند. بنابراین مدیریت انرژی در یک شبکه چند-ریزشبکه ای نیازمند یک چارچوب بهره برداری غیرمتمرکز است تا با ایجاد مشوق های لازم، ریزشبکه ها را تشویق به تراکنش های میان ریزشبکه ای کند. در این مقاله یک چارچوب کاملاً غیرمتمرکز جهت بهبود تاب آوری ریزشبکه ها بر اساس سازماندهی تبادل های رخ به رخ انرژی آنها با درنظرگرفتن انگیزه های مالی مناسب جهت مشارکت ریزشبکه ها پیشنهاد شده است. در مدل پیشنهادی داده های خصوصی هر کدام از ریزشبکه ها مانند اطلاعات بار و منابع تولید پراکنده، در هنگام تسویه بازار محفوظ باقی می ماند. با استفاده از مدل غیرمتمرکز پیشنهادی، ریزشبکه ها می توانند در بستر تبادل های رخ به رخ انرژی، علاوه بر کاهش هزینه های بهره برداری خویش نسبت به حالت جزیره ای، تاب آوری شبکه را نیز افزایش دهند. رویکرد غیرمتمرکز پیشنهادی به کنترل کننده مرکزی نیاز نداشته و سرعت همگرایی بالایی دارد. برای ارزیابی عملکرد روش پیشنهادی، شبیه سازی ها برای یک سیستم دارای چهارده ریزشبکه انجام و نتایج به دست آمده با رویکرد جزیره ای مقایسه شده است. شبیه سازی ها در محیط متلب و با استفاده از جعبه ابزار Yalmip انجام شده است. برای حل مدل برنامه ریزی نیز از CPLEX 12.9 استفاده شده است. نتایج به دست آمده کارآیی روش پیشنهادی در افزایش تاب آوری و کاهش هزینه های بهر ه برداری را نشان داده است. تفاصيل المقالة -
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99 - یک چارچوب سه مرحله‌‌ای برای تعیین استراتژی بهینه ریزشبکهها جهت مشارکت در بازار رقابتی روز بعد با در نظر گرفتن خودروهای الکتریکی و برنامههای پاسخگویی تقاضا
ابوالفضل بیاتیان امیر احمری نژاددر این مقاله یک چارچوب سه مرحله‌‌ای مبتنی بر سناریو برای تعیین استراتژی بهینه و برنامهریزی ریزشبکه‌‌های قرار گرفته در یک سیستم توزیع 118 شینه ارائه شده است. عدم قطعیت‌‌های منابع تجدیدپذیر، تقاضای بار و برنامه شارژ/دشارژ خودروهای الکتریکی در نظر گرفته شده است. برای ارتق أکثردر این مقاله یک چارچوب سه مرحله‌‌ای مبتنی بر سناریو برای تعیین استراتژی بهینه و برنامهریزی ریزشبکه‌‌های قرار گرفته در یک سیستم توزیع 118 شینه ارائه شده است. عدم قطعیت‌‌های منابع تجدیدپذیر، تقاضای بار و برنامه شارژ/دشارژ خودروهای الکتریکی در نظر گرفته شده است. برای ارتقای انعطاف در برنامهریزی، بهرهبردار قادر خواهد بود تا از طریق بازآرایی سیستم توزیع مسیر شارش توان را تغییر دهد. همچنین در مدل پیشنهادی مشترکین قادر به کاهش هزینههای خود از طریق مشارکت در یک برنامه پاسخگویی تقاضا هستند. در مرحله اول مدل پیشنهادی، استراتژی پیشنهادی ریزشبکهها تعیین می شود. در مرحله دوم قیمت تسویه بازار توسط بهرهبردار مستقل سیستم و با توجه به پیشنهادات ارسالی مشخص می گردد. در نهایت، در مرحله سوم مسئله برنامهریزی نهایی ریزشبکهها توسط یک روش تئوری بازی مشارکتی حل میشود. مدل پیشنهادی توسط حل‌کننده CPLEX در نرم‌افزار گمز حل شده و نتایج نشان می‌‌دهند که توپولوژی دینامیک انعطاف برنامهریزی را ارتقا داده و از این طریق منجر به کاهش حدود 10 درصدی هزینه بهره‌‌برداری کل شده است. همچنین نتایج نشان می‌‌دهند که هماهنگی خودروهای الکتریکی با برنامهریزی، حضور سیستمهای ذخیره‌‌ساز و اجرای برنامه پاسخگویی تقاضا منجر به کاهش چشمگیر سطح قیمت تسویه بازار و در نتیجه کاهش هزینههای بهره‌‌برداری میشود. تفاصيل المقالة -
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100 - کران بالای طول صف در روش زمانبندی "سرویس هجومی تنظیم شده"
سید محمود دانشور فرزانگان حسین سعیدیبا توجه به نقش تضمین کیفیت سرویس در شبکه‌های کامپیوتری و مخابراتی جدید برای سرویسهای چند رسانه‌ای، تحقیق بر روی روشهای ارائه سرویس تضمین شده به ترافیک‌های متنوعی که در شبکه‌ها جاری هستند، از جایگاه ویژه‌ای برخوردار است. روشهای زمانبندی در این میان به دلیل نقش مهم‌شان، ب أکثربا توجه به نقش تضمین کیفیت سرویس در شبکه‌های کامپیوتری و مخابراتی جدید برای سرویسهای چند رسانه‌ای، تحقیق بر روی روشهای ارائه سرویس تضمین شده به ترافیک‌های متنوعی که در شبکه‌ها جاری هستند، از جایگاه ویژه‌ای برخوردار است. روشهای زمانبندی در این میان به دلیل نقش مهم‌شان، بیشتر مورد توجه قرار گرفته‌اند. برای ارائه سرویس به جریان‌های ترافیکی هجومی روشی به نام زمانبندی با هجمه تنظیم شده که به اختصار RBSS نامیده شده است، ارائه شده است. مهمترین ویژگی روش RBSS لحاظ نمودن پارامتر هجمه علاوه بر نرخ در کیفیت سرویس است. در این مقاله سعی شده است با یک تحلیل ریاضی به کمک تئوری جبر شبکه، کران بالای طول صف در روش زمانبندی مورد اشاره به دست آید. ویژگی مهم این روش دخالت دادن طول صف در فرآیند تصمیم‌گیری زمانبند است که باعث میشود محاسبه منحنی سرویس به یک نامساوی دیفرانسیلی منجر شود و محاسبه کران بالای طول صف را نسبت به روشهای مشابه با دشواریهای بیشتری روبرو سازد. برای سهولت در محاسبات، در این مقاله فرض کرده‌ایم که منحنی ترافیک ورودی برای هر محاوره حالت خطی داشته باشد تفاصيل المقالة -
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101 - An Improved Optimization Model for Scheduling of a Multi-Product Tree-Like Pipeline
Mehrnoosh TaherkhaniIn the petroleum supply chain, oil refined products are often delivered to distribution centers by pipelines since they provide the most reliable and economical mode of transportation over large distances. This paper addresses the optimal scheduling of a complex pipelin أکثرIn the petroleum supply chain, oil refined products are often delivered to distribution centers by pipelines since they provide the most reliable and economical mode of transportation over large distances. This paper addresses the optimal scheduling of a complex pipeline network with multiple branching lines. The main challenge is to find the optimal sequence and time of product injections/deliveries at input /output nodes in order to satisfy product demands with minimum costs. We propose a mixed integer linear problem (MILP) approach that is capable of detecting the interface volumes in any pipeline and handling the simultaneous deliveries to distribution depots. Numerical examples are solved to validate the proposed model. تفاصيل المقالة -
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102 - Using Theory of Constraints in Production Management and Scheduling (A Case Study)
Ahmad Hooshmand Ali Reza Mehrazeen Ali Reza Davoody Mohamad Reza ShorvarziIn manufacturing institutes the only access way to maximum profit is identifying the production mix of the products based on the limitations such as policies and politics, demand and production processes. This study identifies the constraints of a tile-manufacturing com أکثرIn manufacturing institutes the only access way to maximum profit is identifying the production mix of the products based on the limitations such as policies and politics, demand and production processes. This study identifies the constraints of a tile-manufacturing company including constraints in its production and demand line using LINGO software version 15, and identifying production bottleneck, i.e. furnace, production scheduling was provided and sensitivity analysis was con-ducted on the variables and right hand items. Positive shadow price of furnace shows efficiency of every unit on throughput. Also, in demand constraint, negative shadow price of product 16 shows decreasing effect of increase of every unit on throughput. Allowable increase and decrease of right hand items show allowable increase in furnace section and limitlessness of allowable decrease of product 16. Changes in this range causes that the current basis remains optimal changes in which causes changes in the optimal value of the target function regarding shadow prices. تفاصيل المقالة -
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103 - A Branch and Bound for single machine stochastic batch scheduling with delivery costs. A Chance Constraint approach (Case study in Iran)
حمیدرضا حدادThis paper study a single machine stochastic scheduling problem based on an Iranian real case study in Saipa company in which the objective is to minimize total completion times and delivery costs. According to existence data sets of this company the processing times fo أکثرThis paper study a single machine stochastic scheduling problem based on an Iranian real case study in Saipa company in which the objective is to minimize total completion times and delivery costs. According to existence data sets of this company the processing times follows a Normal distribution and based on the managerial decisions two objectives have to be achieved simultaneously including total completion times and controlling tardiness values so that their values are lower than an specified penalty. So, a Chance Constraint Programming (CCP) approach is employed and a mathematical model is presented. In order to solve the problem a Branch and Bound (B&B) method is used to solve the problem optimally and a Particle Swarm Optimization (PSO) metaheuristic is used to find near optimal solutions for large scales. The results show that using the proposed mathematical model and solution approach, could increase the effectiveness and efficiency of production line as 16 to 40 percent. Computational experiments validate the accuracy of proposed method. تفاصيل المقالة -
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104 - Presenting a Mathematical Programming Model for Routing and Scheduling of Cross-Dock and Transportation in Green Reverse Logistics Network of COVID-19 Vaccines
Pezhman Abbasi Tavallali محمدرضا فیلی زاده Atefeh AmindoustCross-docking is the practice of unloading Coronavirus vaccines from inbound delivery vehicles and loading them directly onto outbound vehicles. Cross-docking can streamline supply chains and help them move Coronavirus vaccines to pharmacies faster and more efficiently أکثرCross-docking is the practice of unloading Coronavirus vaccines from inbound delivery vehicles and loading them directly onto outbound vehicles. Cross-docking can streamline supply chains and help them move Coronavirus vaccines to pharmacies faster and more efficiently by eliminating or minimizing warehouse storage costs, space requirements, and inventory handling. Regarding their short shelf-life, the movement of Coronavirus vaccine to cross-dock and their freight scheduling is of great importance. Achieving the goals of green logistics in order to reduce fuel consumption and emission of pollutants has been considered in this study. Accordingly, the present study developed a mixed-integer linear programming (MILP) model for routing and scheduling of cross-dock and transportation in green reverse logistics network of Coronavirus vaccines. The model was multi-product and multi-level and focused on minimizing the logistics network costs to increase efficiency, reduce fuel consumption and pollution, maximizing the consumption value of delivered Coronavirus vaccines and minimizing risk of injection complication due to Coronavirus vaccines corruption. Considering cost minimization (i.e., earliness and tardiness penalty costs of pharmacies order delivery, cost of fuel consumption and environmental pollution caused by outbound vehicles crossover, the inventory holding costs at the temporary storage area of the cross-dock and costs of crossover and use of outbound vehicles) as well as uncertainty in pharmacies demand for Coronavirus vaccines, the model was an NP-hard problem. In this model, the problem-solving time increased exponentially according to the problem dimensions; hence, this study proposed an efficient method using the NSGA II algorithm. تفاصيل المقالة -
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105 - GASA: Presentation of an Initiative Method Based on Genetic Algorithm for Task Scheduling in the Cloud Environment
Somayeh Taherian Dehkordi Vahid Khatibi BardsiriThe need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud effic أکثرThe need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud efficiency is an important subject of consideration. Heterogeneity and diversity among different resources and requests of users in the Cloud computing environment creates complexities and problems in task scheduling in the cloud environment. Scheduling consists of selecting the most appropriate resource with the aim to distribute load in resources, and maximum productivity from them, while it should minimize the response time and the time of completion of each task, as well as minimizing the service costs. In addition to analyzing the Cloud computing system and scheduling aspects in it, it has been tried in this article to provide a combined algorithm for appropriate mapping of tasks to the existing virtual machines for reducing the completing times and increasing the productivity of virtual machines. According to the scheduling parameters, the presented method improves the load balancing according to the Sufferage and genetic algorithm as compared to previous algorithms, while it also reduces the total time of requests. The results of simulating the proposed algorithm in CloudSim environment and comparing it with the studied methods show that the proposed algorithm has reached a more optimized response, both for the load balancing and also for the total completion time. تفاصيل المقالة -
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106 - A new Shuffled Genetic-based Task Scheduling Algorithm in Heterogeneous Distributed Systems
Mirsaeid HosseiniDistributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power co أکثرDistributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user response time and underlying resource utilization. Such heterogeneous distributed systems have interconnected different processors with different speed and architecture. Also, the user application which is typically presented in the form of directed acyclic graph (DAG) must be executed on this type of parallel processing systems. Since task scheduling in such complicated systems belongs to NP-hard problems, existing heuristic approaches are no longer efficient. Therefore, the trend is to apply hybrid meta-heuristic approaches. In this paper, we extend a meta-heuristic shuffled genetic-based task scheduling algorithm to minimize total execution time, makespan, of user application. In this regard, we take benefit of other heuristics such as Heterogeneous Earliest Finish Time (HEFT) approach to generate smart initial population by applying a new shuffle operator which makes a fortune to explore feasible and promising individuals in the search space. We also conduct other genetic operators in right way to produce final near to optimal solution. To reach concrete results we have conducted several scenarios. Our proposed algorithm outperforms in term of average makespan compared with other existing approaches such as HEFT versions and QGARAR. تفاصيل المقالة -
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107 - Scheduling of Real-time Processes Distribution on Multiprocessor Using Meta-Heuristic Ant Colony Algorithms, Genetics and PSO
Mostafa Soleymani Hossein NematzadehHere we discuss the problem of distribution of Real_time processes on multiprocessor with on-time maximum job accomplished. Scientists have been searching for producing optimized scheduling.this is an example of NP problems.this is not practical to approach this kind of أکثرHere we discuss the problem of distribution of Real_time processes on multiprocessor with on-time maximum job accomplished. Scientists have been searching for producing optimized scheduling.this is an example of NP problems.this is not practical to approach this kind of problems with heuristic approach thus we must use meta-heuristic algorithms.These algorithms present many sets of answers in order to make options for scheduler, to choose the best process assignment to processor. Two examples are Branch and Bound, and Task Graph Algorithms. By studying the ant colony,Genetics and PSO Algorithms, we will design and consider several methods for our purpose and use them to produce Job assignment Scheduler, on processors. Each of these algorithms will provide us with a specific designing method and help us to make a scheduler engine of real_time processes assignment on processors. We will compare each program to the first heuristic one, to assess the manufactured programs. In comparisons which are based on lost processes, Colony approach has 11.94 % ,PSO approach 11.19 %, and Genetic approach has 7.52 % less process lost in compare to heuristic approach. It worth mention that 20 files each of which containing 50 Real_time process have been used In these experiments. تفاصيل المقالة -
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108 - An Efficient Genetic Algorithm for Task Scheduling on Heterogeneous Computing Systems Based on TRIZ
Mehdi AkbariAn efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic methods for finding a suboptim أکثرAn efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic methods for finding a suboptimal schedule. In this paper we proposed a new approach using TRIZ (specially 40 inventive principles). The basic idea of this approach is to exploit the advantages of heuristic-based algorithms to reduce space search and the time needed to find good solutions. The proposed algorithm improves the performance of genetic algorithm through significant changes in its genetic functions and introduction of new operators that guarantee sample variety and consistent coverage of the whole space. The achieved results of running this algorithm on the graphs of real-world applications and random graphs in heterogeneous computing systems with a wide range of characteristics, indicated significant improvements of efficiency of the proposed algorithm compared with other task scheduling algorithms. Although the proposed algorithm needs lower repetitions than their genetic counterparts, it needs high frequency of repetition to produce the desired answer. This is a drawback for this algorithm compared to heuristic algorithms such as CPOP and HEFT. تفاصيل المقالة -
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109 - Task Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
Mona TorabiIn this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme an أکثرIn this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to appropriate resources. The proposed method has less Makespan and price. In addition to implementing a grid computing system, the proposed method which is using three standard test functions in evolutionary multi-objective optimization is evaluated. In this paper, the number of elements in the assessment of the Pareto optimizes set, uniformity and error. The results show that this Search method has more optimization in particle number density and high accuracy with less error than the MOPSO and can be replaced as an effective solution for solving multi-objective optimization. تفاصيل المقالة -
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110 - Solving the Job Scheduling Problem in Open Shop Using Bat Algorithm
Sima SivandiAn optimal scheduling reduces the completion time (makespan) of jobs, and finally increase profits in today's competitive environment. Open shop scheduling problem (OSSP) involves a set of activities that should be performed on a limited set of machines. The aim of sche أکثرAn optimal scheduling reduces the completion time (makespan) of jobs, and finally increase profits in today's competitive environment. Open shop scheduling problem (OSSP) involves a set of activities that should be performed on a limited set of machines. The aim of scheduling in an open shop is to provide a schedule for the execution of the entire operation so that the completion time of all operations is reduced. OSSP has a large solution space and belongs to NP-hard problems. So far, various algorithms are developed for OSSP. In this paper we propose a new optimization algorithm named Bat Algorithm (BA) for solving OSSP which has a relative advantage over other algorithms. Experimental results show that the proposed algorithm has high performance and increases the reliability and efficiency of the system. تفاصيل المقالة -
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111 - A Hybrid Genetic Algorithm for the Open ShopScheduling with Makespan and Total Completion Time
Behnam Barzegar Homayun Motameni Ali Khosrozadeh ghomi Azadeh DivsalarProper scheduling of tasks leads to optimum using of time and resources, in order to obtaining best result. One of the most important and complicated scheduling problems is open shop scheduling problem. There are n jobs in open shop scheduling problem which should be pr أکثرProper scheduling of tasks leads to optimum using of time and resources, in order to obtaining best result. One of the most important and complicated scheduling problems is open shop scheduling problem. There are n jobs in open shop scheduling problem which should be processed by m machines. Purpose of scheduling open shop problem is attaining to a suitable order of processing jobs by specified machines so that makespan can be minimized. Open shop scheduling problem has very large and complex solution space and so is one of NP-Problems. Till now, different algorithms have been presented for open shop scheduling problem. In this paper, we have used combined genetics algorithm as a strategy for solving scheduling open shop problem and compared proposed algorithm with DGA algorithm. Results show that the proposed algorithm has better effectiveness than DGA algorithm. تفاصيل المقالة -
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112 - Task Scheduling in Fog Computing: A Survey
Abbas Najafizadeh Afshin Salajegheh Amir Masoud Rahmani Amir SahafiRecently, fog computing has been introducedto solve the challenges of cloud computing regarding Internet objects. One of the challenges in the field of fog computing is the scheduling of tasks requested by Internet objects. In this study, a review of articles related to أکثرRecently, fog computing has been introducedto solve the challenges of cloud computing regarding Internet objects. One of the challenges in the field of fog computing is the scheduling of tasks requested by Internet objects. In this study, a review of articles related to task scheduling in fog computing has been done. At first, the research questions and goals will be introduced, and then we will explain the process of finding and selecting the articles. A comprehensive analysis of the articles will be done. We have identified and listed 10 optimization metrics. Also, according to our study, in 79% of the studied articles, the mathematical model was used to express the problem. In 42% of the articles meta-heuristic algorithms proposed and 84% evaluated their algorithm by simulation. Finally, this paper presents the challenges and open issues of task scheduling in fog computing to the researchers. تفاصيل المقالة -
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113 - Solving Flexible Job-Shop Scheduling Problem using Hybrid Algorithm Based on Gravitational Search Algorithm and Particle Swarm Optimization
Behnam Barzegar Homayun MotameniJob Shop scheduling problem has significant importance in many researching fields such as production management and programming and also combined optimizing. Job Shop scheduling problem includes two sub-problems: machine assignment and sequence operation performing. In أکثرJob Shop scheduling problem has significant importance in many researching fields such as production management and programming and also combined optimizing. Job Shop scheduling problem includes two sub-problems: machine assignment and sequence operation performing. In this paper combination of particle swarm optimization algorithm (PSO) and gravitational search algorithm (GSA) have been presented for solving Job Shop Scheduling problem with criteria of minimizing the maximal completion time of all the operations, which is denoted by Makespan. In this combined algorithm, first gravitational search algorithm finds best mass with minimum spent time for a job and then particle swarm Optimization algorithm is performed for optimal processing all jobs.experimental results show that proposed algorithm for solving job shop scheduling problem, especially for solving larger problem presents better efficiency. Combined proposed algorithm has been named GSPSO. تفاصيل المقالة -
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114 - Evaluating of Feasible Solutions on Parallel Scheduling Tasks with DEA Decision Maker
Mirsaeid Hosseini ShirvaniThis paper surveys parallel scheduling problems and metrics correlated to and then applys metrics to make decision in comparison to other policy schedulers. Parallel processing is new trend in computer science especially in embedded and multicore systems whereas needs m أکثرThis paper surveys parallel scheduling problems and metrics correlated to and then applys metrics to make decision in comparison to other policy schedulers. Parallel processing is new trend in computer science especially in embedded and multicore systems whereas needs more power consumption to reach speed up. The QOS requirement for users is to have good responsiveness and for service providers or system owners to have high throughput and low power consumption in parallel processing or embedded multicore systems. Moreover, fairness is vital issue to make decision wether the scheduler is good or not. Using the metrics is very intricate because misleadling metrics will cause to lose performance and system utility that is why the metrics has been opted cautiously in this paper. However, satisfying all of the objects in which have potentially conflicts is computationally NP-Hard. So, tradeoff between metrics is needed. This paper indicates DEA FDH model based on linear programming that will select the optimal scheduling near to exact solution تفاصيل المقالة -
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115 - Modelling and robust scheduling of two-stage assembly flow shop under uncertainty in assembling times
Maryam seyedhamzeh hossein amoozad khalili Seyed Mohammad Hassan Hosseini mortaza honarmand azimi Kamaladdin RahmaniThis paper focuses on robust scheduling for an assembly flow shop where assembling times are uncertain. The considered manufacturing environment is a two-stage production system that consists of a processing stage followed by an assembly stage. There are two parallel ma أکثرThis paper focuses on robust scheduling for an assembly flow shop where assembling times are uncertain. The considered manufacturing environment is a two-stage production system that consists of a processing stage followed by an assembly stage. There are two parallel machines in the first stage to process the components followed by an assembly stage wherein, the components are assembled to products. The majority of scheduling research considers a deterministic environment with pre-known and fixed data. However, in real-world condition, several kinds of uncertainties should be considered. In this article, the scheduling problem is tackle under uncertainty and the assembling time of each product at the second stage is the source of uncertainty. The problem is described and formulated as a mixed-integer linear programing model under deterministic condition. After that, the uncertainty issue is discussed and the robust scheduling procedure is introduced to minimize the maximum completion time of all products based on the min–max regret approach. To solve the robust scheduling an exact method is proposed to solve the problem on the small scales. Moreover, two approximate methods are modified and used to solve this NP-hard problem on the small and practical scales. The performances of the proposed methods are evaluated by several numerical examples taken from valid references. Computational results indicate that the proposed robust scheduling methods provide effective hedges against processing time uncertainty while maintaining excellent expected makespan performance. تفاصيل المقالة -
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116 - Aircraft routing problem considering various maintenance operation factors: A literature review
Masoumeh Mirjafari Alireza Rashidi Komijan Ahmad ShojaThe companies in the aviation industry require exact scheduling and operation due to their complex and costly activities. The aircraft routing problem (ARP) which meets all of the requirements related to maintenance operations and achieves the minimum costs is among the أکثرThe companies in the aviation industry require exact scheduling and operation due to their complex and costly activities. The aircraft routing problem (ARP) which meets all of the requirements related to maintenance operations and achieves the minimum costs is among the significant issues for an airline. Solving the ARP includes creating all of the routes and defining aircraft maintenance inspections. The present study aims to review and categorize the recent research on ARP and maintenance operation. To this aim, four significant categories including type of model, maintenance and repair factors, disruption and robustness, as well as objective function and solution approach were defined. Based on the literature review, the integrated study of the airline schedule steps provides better results than the multi-stage review. In addition, defining the combined framework of different maintenance factors generates a more accurate schedule to control the maintenance requirements. Further, applying multiple hybrids meta-heuristic approach leads to significant results. تفاصيل المقالة -
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117 - Improved TLBO and JAYA algorithms to solve new fuzzy flexible job-shop scheduling problems
Raviteja Buddala Siba Sankar Mahapatra Manas Ranjan Singh Bhanu Chandar Balusa Purusotham Singamsetty Venkata Phanikrishna BalamFlexible job-shop scheduling problem (FJSP) finds significant interest in the field of scheduling in dealing with complexity, solution methodology and, industrial applications. However, most of the studies on FJSP, consider the processing time of operations to be determ أکثرFlexible job-shop scheduling problem (FJSP) finds significant interest in the field of scheduling in dealing with complexity, solution methodology and, industrial applications. However, most of the studies on FJSP, consider the processing time of operations to be deterministic and known at priori while solving the problem. Since uncertainty is bound to occur in industries, deterministic approaches for solving FJSP may not yield good solutions. Schedules generated considering uncertainties may help the manufacturing firms to handle the uncertainties efficiently. The present work aims at solving FJSP in a realistic manner, considering uncertainty in the processing times. A modified version of optimization algorithms without tuning parameters such as teaching-learning-based optimization (TLBO) and JAYA is proposed to solve fuzzy FJSP (FFJSP) with less computational burden. Although there are enough challenging benchmark problems for deterministic FJSP problems, only limited benchmarks are available for a fuzzy variant of FJSP. The currently available FFJSP problems in the literature are small in size as compared to Brandimate data instances which are widely accepted for a deterministic variant of FJSP. Therefore, an attempt has been made in this paper to solve the instances of Kacem’s and Brandimarte’s by converting them into fuzzy FJSP. The present work also provides new challenging problems compared to the existing benchmark problems to study FFJSP. تفاصيل المقالة -
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118 - A multi-product, multi-period and multi-hub routing and scheduling model for offshore logistics
Alireza Rashidi Komijan Mehdi Razi Peyman Afzal Vahidreza Ghezavati Kaveh Khalili DamghaniLogistics in upstream oil industry is a critical task as rigs need consistent support for ongoing production. In this paper, a multi-period, multi-product and multi-hub routing and scheduling model is presented for offshore logistics problem. As rigs can be served in sp أکثرLogistics in upstream oil industry is a critical task as rigs need consistent support for ongoing production. In this paper, a multi-period, multi-product and multi-hub routing and scheduling model is presented for offshore logistics problem. As rigs can be served in specific time intervals, time windows constraints are considered in the proposed model. Despite classic VRP models, vessels are not forced to return hubs at the end of duty days. Also, a vessel may leave and return back to hubs several times during the planning horizon. Moreover, the model determines which vessels are applied in each day. In other words, a vessel may be applied in some days and be inactive in other days of planning horizon. To develop a compromise model, fueling issue is considered in the model. As a rig can be supplied by different vessels in real world cases, the proposed model is split delivery. Based on these challenges and contributions, this research deploys an integrated optimization of routing and scheduling of vessels for offshore logistics. This paper deals with a combinatorial optimization model which is NP-hard. Hence, Genetic Algorithm is applied as the solution approach. The average gap between objective functions of GAMS and GA is only 1.18 percent while saving CPU time in GA is much more than GAMS (about 78.16 percent on average). The results confirm the applicability and efficiency of the GA. تفاصيل المقالة -
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119 - Robust Scheduling and Planning of Operating Rooms and Sterilization Unit with Emergency and Elective Patients: Two Metaheuristic Algorithms
Fatemeh Arjmandi Parvaneh SamoueiGreat attention should be paid to planning and scheduling surgeries in the operating room which is the most sensitive ward in the health context in terms of cost and specific sensitivity due to its association with the life and death of individuals. In this case, reusab أکثرGreat attention should be paid to planning and scheduling surgeries in the operating room which is the most sensitive ward in the health context in terms of cost and specific sensitivity due to its association with the life and death of individuals. In this case, reusable sterile equipment and devices are crucial issues because the hospital or nosocomial infections result from insufficient sterilization of these instruments. Therefore, sterilization of reusable medical devices is a necessity in the operating room to prevent possible infections. This study solves the integrated operating rooms and sterile section planning problem to minimize the total costs of sterilization, surgery postponement, and performance. This study also minimizes the completion time of surgery considering nondeterministic operating times and emergency-elective patients. In the real world, surgery time may be nondeterministic based on the conditions of the patient, surgeon, equipment, and instruments; hence, it is valuable to find a robust solution for planning under such circumstances. After presenting a bi-objective mathematical model for this problem, an improved epsilon constraint method was used to solve problems with small dimensions, and two metaheuristics NSGA-II and NRGA were developed for large dimensions regarding NP-hard problems. These two algorithms were analysed in terms of five indicators. The results indicated the superiority of the NSGA-II algorithm over NRGA to solve such problems. تفاصيل المقالة -
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120 - An electromagnetism-like metaheuristic for open-shop problems with no buffer
Bahman Naderi Esmaeil Najafi Mehdi YazdaniThis paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mix أکثرThis paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic based on an electromagnetism algorithm to solve the large-sized problems. The paper conducts two computational experiments. The first includes small-sized instances by which the mathematical model and general performance of the proposed metaheuristic are evaluated. The second evaluates the metaheuristic for its performance to solve some large-sized instances. The results show that the model and algorithm are effective to deal with the problem. تفاصيل المقالة -
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121 - A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem
Mohammad Mirabi S. M. T. Fatemi Ghomi F . JolaiFlow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and أکثرFlow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this paper develops a novel hybrid genetic algorithm (HGA) with three genetic operators. Proposed HGA applies a modified approach to generate a pool of initial solutions, and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. We consider the make-to-order production approach that some sequences between jobs are assumed as tabu based on maximum allowable setup cost. In addition, the results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution. تفاصيل المقالة -
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122 - Dynamic configuration and collaborative scheduling in supply chains based on scalable multi-agent architecture
Fu-Shiung HsiehDue to diversified and frequently changing demands from customers, technological advances and global competition, manufacturers rely on collaboration with their business partners to share costs, risks and expertise. How to take advantage of advancement of technologies t أکثرDue to diversified and frequently changing demands from customers, technological advances and global competition, manufacturers rely on collaboration with their business partners to share costs, risks and expertise. How to take advantage of advancement of technologies to effectively support operations and create competitive advantage is critical for manufacturers to survive. To respond to these challenges, development of a dynamic scheme to better manage collaborative workflows is urgent. In this paper, we will study how to develop a flexible and scalable framework to dynamically and coherently configure workflows that can meet order requirements based on multi-agent systems (MAS). Configuring and scheduling collaborative workflows is a challenging problem due to the computational complexity involved, distributed architecture and dependency among different partners’ workflows. To achieve flexibility and reduce the cost and time involved in configuration of a supply chain network, we propose an approach that combines MAS, contract net protocol, workflow models and automated transformation of the workflow models to dynamically formulate the scheduling problem. To attain scalability, we develop a solution algorithm to solve the optimization problem by a collaborative and distributed computation scheme. We implement a software system based on industrial standards, including FIPA and the Petri net workflow specification model. In addition, we also illustrate effectiveness and analyze scalability of our approach by examples. Our approach facilitates collaboration between partners and provides a scalable solution for the increasing size of supply chain networks. تفاصيل المقالة -
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123 - Cat swarm optimization for solving the open shop scheduling problem
Abdelhamid Bouzidi Mohammed Essaid Riffi Mohammed BarkatouThis paper aims to prove the efficiency of an adapted computationally intelligence-based behavior of cats called the cat swarm optimization algorithm, that solves the open shop scheduling problem, classified as NP-hard which its importance appears in several industrial أکثرThis paper aims to prove the efficiency of an adapted computationally intelligence-based behavior of cats called the cat swarm optimization algorithm, that solves the open shop scheduling problem, classified as NP-hard which its importance appears in several industrial and manufacturing applications. The cat swarm optimization algorithm was applied to solve some benchmark instances from the literature. The computational results, and the comparison of the relative percentage deviation of the proposed metaheuristic with other’s existing in the literature, show that the cat swarm optimization algorithm yields good results in reasonable execution time. تفاصيل المقالة -
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124 - Optimisation of assembly scheduling in VCIM systems using genetic algorithm
Son Duy Dao Kazem Abhary Romeo MarianAssembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the app أکثرAssembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the application of traditional computer-integrated manufacturing (CIM) system to global level. Assembly scheduling in VCIM systems is quite different from one in traditional production systems because of the difference in the working principles of the two systems. In this article, the assembly scheduling problem in VCIM systems is modeled and then an integrated approach based on genetic algorithm (GA) is proposed to search for a global optimised solution to the problem. Because of dynamic nature of the scheduling problem, a novel GA with unique chromosome representation and modified genetic operations is developed herein. Robustness of the proposed approach is verified by a numerical example. تفاصيل المقالة -
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125 - Maximizing the nurses’ preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm
Hamed Jafari Nasser SalmasiThe nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital’s demand during the planning horizon by considering different objective functions. أکثرThe nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital’s demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses’ preferences for working shifts and weekends off by considering several important factors such as hospital’s policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49% compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses. تفاصيل المقالة -
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126 - New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times
Hamidreza Kia Seyed Hassan Ghodsypour Hamid DavoudpourIn the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable p أکثرIn the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0–1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others. تفاصيل المقالة -
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127 - A heuristic approach for multi-stage sequence-dependent group scheduling problems
N SalmasiWe present several heuristic algorithms based on tabu search for solving the multi-stage sequence-dependent group scheduling (SDGS) problem by considering minimization of makespan as the criterion. As the problem is recognized to be strongly NP-hard, several meta (tabu) أکثرWe present several heuristic algorithms based on tabu search for solving the multi-stage sequence-dependent group scheduling (SDGS) problem by considering minimization of makespan as the criterion. As the problem is recognized to be strongly NP-hard, several meta (tabu) search-based solution algorithms are developed to efficiently solve industry-size problem instances. Also, two different initial solution generators are developed to aid in the application of the tabu search-based algorithms. A lower bounding technique based on relaxing the mathematical model for the original SDGS problem is applied to estimate the quality of the heuristic algorithms. To find the best heuristic algorithm, random test problems, ranging in size from small, medium, to large are created and solved by the heuristic algorithms. A detailed statistical experiment, based on nested split-plot design, is performed to find the best heuristic algorithm and the best initial solution gen-erator. The results of the experiment show that the tabu search-based algorithms can provide high quality so-lutions for the problems with an average percentage error of only 1.00%. تفاصيل المقالة -
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128 - Locomotive assignment problem with train precedence using genetic algorithm
Siamak Noori Seyed Farid GhannadpourThis paper aims to study the locomotive assignment problem which is very important for railway companies, in view of high cost of operating locomotives. This problem is to determine the minimum cost assignment of homogeneous locomotives located in some central depots to أکثرThis paper aims to study the locomotive assignment problem which is very important for railway companies, in view of high cost of operating locomotives. This problem is to determine the minimum cost assignment of homogeneous locomotives located in some central depots to a set of pre-scheduled trains in order to provide sufficient power to pull the trains from their origins to their destinations. These trains have different degrees of priority for servicing, and the high class of trains should be serviced earlier than others. This problem is modeled using vehicle routing and scheduling problem where trains representing the customers are supposed to be serviced in pre-specified hard/soft fuzzy time windows. A two-phase approach is used which, in the first phase, the multi-depot locomotive assignment is converted to a set of single depot problems, and after that, each single depot problem is solved heuristically by a hybrid genetic algorithm. In the genetic algorithm, various heuristics and efficient operators are used in the evolutionary search. The suggested algorithm is applied to solve the medium sized numerical example to check capabilities of the model and algorithm. Moreover, some of the results are compared with those solutions produced by branch-and-bound technique to determine validity and quality of the model. Results show that suggested approach is rather effective in respect of quality and time. تفاصيل المقالة -
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129 - Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Hamid Sattari Garmdare M. M . Lotfi Mahboobeh HonarvarUsually, in make-to-order environments which work only in response to the customer’s orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer’s sensitivity أکثرUsually, in make-to-order environments which work only in response to the customer’s orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer’s sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out. تفاصيل المقالة -
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130 - Minimizing the total tardiness and makespan in an open shop scheduling problem with sequence-dependent setup times
Samaneh Noori-Darvish Reza Tavakkoli-MoghaddamWe consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathe أکثرWe consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEAII. Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the traditional NSGA-II. تفاصيل المقالة -
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131 - A fuzzy mixed-integer goal programming model for a parallel machine scheduling problem with sequence-dependent setup times and release dates
A.H GharehgozliThis paper presents a new mixed-integer goal programming (MIGP) model for a parallel machine scheduling problem with sequence-dependent setup times and release dates. Two objectives are considered in the model to minimize the total weighted flow time and the total weigh أکثرThis paper presents a new mixed-integer goal programming (MIGP) model for a parallel machine scheduling problem with sequence-dependent setup times and release dates. Two objectives are considered in the model to minimize the total weighted flow time and the total weighted tardiness simultaneously. Due to the com-plexity of the above model and uncertainty involved in real-world scheduling problems, it is sometimes unre-alistic or even impossible to acquire exact input data. Hence, we consider the parallel-machine scheduling problem with sequence-dependent set-up times under the hypothesis of fuzzy processing time`s knowledge and two fuzzy objectives as the MIGP model. In addition, a quite effective and applicable methodology for solving the above fuzzy model is presented. At the end, the effectiveness of the proposed model and the de-noted methodology is demonstrated through some test problems. تفاصيل المقالة -
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132 - JIT single machine scheduling problem with periodic preventive maintenance
Mohammadreza Shahriari Naghi Shoja Amir Ebrahimi Zade Sasan Barak Mani SharifiThis article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer أکثرThis article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms’ parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms. تفاصيل المقالة -
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133 - An improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling
Son Duy Dao Kazem Abhary Romeo MarianIntegration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensi أکثرIntegration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to “learn” from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers. تفاصيل المقالة -
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134 - Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model
Houssem Eddine Nouri Olfa Belkahla Driss Khaled Ghe´diraThe flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which a أکثرThe flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach. تفاصيل المقالة -
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135 - A three-stage assembly flow shop scheduling problem with blocking and sequence-dependent set up times
Aref Maleki-Darounkolaei Mahmoud Modiri Reza Tavakkoli-Moghaddam Iman SeyyediThis paper considers a three-stage assembly flowshop scheduling problem with sequence-dependent setup < /div> times at the first stage and blocking times between each stage in such a way that the weighted mean completion time and makespan are minimized. Obtaining أکثرThis paper considers a three-stage assembly flowshop scheduling problem with sequence-dependent setup < /div> times at the first stage and blocking times between each stage in such a way that the weighted mean completion time and makespan are minimized. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time using traditional approaches or optimization tools is extremely difficult. Thus, this paper proposes a meta-heuristic method based on simulated annealing (SA) in order to solve the given problem. Finally, the computational results are shown and compared in order to show the efficiency of our proposed SA. تفاصيل المقالة -
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136 - Nurse rostering using fuzzy logic: A case study
A Eskandari K ZiaratiIn this paper, we used the fuzzy set theory for modeling flexible constraints and uncertain data in nurse scheduling problems and proposed a fuzzy linear model for nurse rostering problems. The developed model can produce rosters that satisfy hospital objectives, ward r أکثرIn this paper, we used the fuzzy set theory for modeling flexible constraints and uncertain data in nurse scheduling problems and proposed a fuzzy linear model for nurse rostering problems. The developed model can produce rosters that satisfy hospital objectives, ward requirements and staff preferences by satisfying their requests as much as possible. Fuzzy sets are used for modeling demands of personnel in each shift. The objective is to identify the optimum roster for nurses in order to complete the weekly roster with fuzzy constraints. This model is implemented for the data collected from Namazi Hospital (NH) of Shiraz, which is the largest hospital in the south of Iran. After modeling, this problem is solved by using Lingo software. Finally we compare the result of fuzzy rosters with goal programming rosters that we have previously modeled and with manual rosters that are produced by the head nurses of NH. تفاصيل المقالة -
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137 - Techniques for cash management in scheduling manufacturing operations
Mehdy Morady Gohareh Naser Shams Gharneh Reza Ghasemy YaghinThe objective in traditional scheduling is usually time based. Minimizing the makespan, total flow times, total tardi costs, etc. are instances of these objectives. In manufacturing, processing each job entails a cost paying and price receiving. Thus, the objective shou أکثرThe objective in traditional scheduling is usually time based. Minimizing the makespan, total flow times, total tardi costs, etc. are instances of these objectives. In manufacturing, processing each job entails a cost paying and price receiving. Thus, the objective should include some notion of managing the flow of cash. We have defined two new objectives: maximization of average and minimum available cash. For single machine scheduling, it is demonstrated that scheduling jobs in decreasing order of profit ratios maximizes the former and improves productivity. Moreover, scheduling jobs in increasing order of costs and breaking ties in decreasing order of prices maximizes the latter and creates protection against financial instability. تفاصيل المقالة -
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138 - Scheduling of flexible manufacturing systems using genetic algorithm: A heuristic approach
Vijay Kumar A. N. Narashima Murthy Krishnappa ChandrashekaraScheduling of production in Flexible Manufacturing Systems (FMSs) has been extensively investigated over the past years and it continues to attract the interest of both academic researchers and practitioners. The generation of new and modified production schedules is be أکثرScheduling of production in Flexible Manufacturing Systems (FMSs) has been extensively investigated over the past years and it continues to attract the interest of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today’s complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial schedule. Uncertainties in the production environment and modeling limitations inevitably result in deviations from the generated schedules. This makes rescheduling or reactive scheduling essential. One of the four different types of uncertainties that normally cause discrepancies between the actual output and the planned output is considered in this paper. These include unforeseen machine break-downs, increased order priority, rush orders arrival and order cancellations. In this paper, the current status of the shop is considered while rescheduling. The proposed algorithms revise only those operations that must be rescheduled and can, therefore, be used in conjunction with the existing scheduling methods to improve the efficiency of flexible manufacturing systems. تفاصيل المقالة -
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139 - Lot sizing with rework and different inspection costs
Rasoul Haji Alireza HajiThis paper deals with the single machine multi-product lot scheduling problem in which defective items are produced in any production run of each product. We have adopted the common cycle scheduling policy and assumed that the setup times for production of each product أکثرThis paper deals with the single machine multi-product lot scheduling problem in which defective items are produced in any production run of each product. We have adopted the common cycle scheduling policy and assumed that the setup times for production of each product can be non-zero. Further, we have assumed that defective items will be reworked and the inspection costs during the normal production and rework proc-essing times are different. For this system we obtained the optimal batch sizes for each product such that the total cost per unit time is minimized. تفاصيل المقالة -
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140 - Splittable stochastic project scheduling with constrained renewable resource
S.S Hashemin S.M.T Fatemi GhomiThis paper discusses the problem of allocation of constrained renewable resource to splittable activities of a single project. If the activities of stochastic projects can be split, these projects may be completed in shorter time when the available resource is constrain أکثرThis paper discusses the problem of allocation of constrained renewable resource to splittable activities of a single project. If the activities of stochastic projects can be split, these projects may be completed in shorter time when the available resource is constrained. It is assumed that the resource amount required to accom-plish each activity is a discrete quantity and deterministic. The activity duration time is assumed to be a dis-crete random variable with arbitrary experimental distribution. Solving stochastic mathematical programming model of problem is very hard. So, here some existing methods for deterministic problems have been gener-alized for stochastic case. Solutions of generalized methods are relatively better than random solutions. How-ever, the authors developed the new algorithm that may improve the solutions of generalized methods and project Completion Time Distribution Function (CTDF). Comparison of solution of a method with random solutions is a common assessment method in literature research. Hence, the efficiency of the proposed algo-rithm represented using this method. تفاصيل المقالة -
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141 - A genetic algorithm approach for problem
E Mehdizadeh R Tavakkoli-MoghaddamIn this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). No set-up is necessary between jobs belonging to the same family. A set-up must be scheduled when أکثرIn this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). No set-up is necessary between jobs belonging to the same family. A set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i j, the duration of this set-up being the sequence-independent set-up time sj for family j. This problem is shown to be NP-hard in the strong sense and obtaining an optimal solution for the large-sized problems in reasonable computational time is extremely difficult. Further, it is computationally evaluated the performance of the proposed genetic algorithm solutions obtained using a mixed integer programming (MIP) with the Lingo 8.0 software. تفاصيل المقالة -
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142 - Yard crane scheduling in port container terminals using genetic algorithm
H Javanshir S.R Seyedalizadeh GanjiYard crane is an important resource in container terminals. Efficient utilization of the yard crane significantly improves the productivity and the profitability of the container terminal. This paper presents a mixed integer programming model for the yard crane scheduli أکثرYard crane is an important resource in container terminals. Efficient utilization of the yard crane significantly improves the productivity and the profitability of the container terminal. This paper presents a mixed integer programming model for the yard crane scheduling problem with non- interference constraint that is NPHARD in nature. In other words, one of the most important constraints in this model which we can mention to yard crane non- interference constraint is that they usually move on the same rails in the yard block. Optimization methods, like branch and bound algorithm, has no sufficient efficiency to solve this model and become perfectly useless when the problem size increases. In this situation, using an advanced search method like genetic algorithm (GA) may be suitable. In this paper, a GA is proposed to obtain near optimal solutions. The GA is run by MATLAB 7.0 and the researchers used LINGO software which benefits from the Branch and Bound algorithm for comparing outputs of GA and the exact solution. We should consider the abilities of the LINGO software which is not capable of solving the problems larger than 5 slots to 3 yard cranes. The computational results show that the proposed GA is effective and efficient in solving the considered yard crane scheduling problem. تفاصيل المقالة -
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143 - An algorithm for multi-objective job shop scheduling problem
Parviz Fattahi Mohammad Saidi Mehrabad Mir B. AryanezhadScheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational com أکثرScheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we propose a Pareto approach to solve multi-objective job shop scheduling. The objective considered is to minimize the overall completion time (makespan) and total weighted tardiness (TWT). An effective simulated annealing algorithm based on proposed approach is presented to solve multi-objective job shop scheduling problems. An external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the problem solving process. The parameters in the proposed algorithm are determined after conducting a pilot study. Numerical examples are used to evaluate and study the performance of the proposed algorithm. تفاصيل المقالة -
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144 - Flexible job shop scheduling under availability constraints
M.T Taghavi-Fard H.R Dehnar SaidyIn this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all أکثرIn this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. This study seems utterly new and it is applicable to any performance measure based on the completion time. The investigated models are very close to the actual scheduling problems, because they envisage the flexible job shop environments, heads, set-up times, arbitrary number of unavailability periods on all resources, arbitrary number of work-centers, any kind of cross-ability, any kind of resume-ability and several types of performance measures. The proposed model is presented to solve two-job problems because it is a graphical approach. However, it is concluded that the idea can be extended to n-dimensional problems as well. تفاصيل المقالة -
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145 - Technical Note: An opportunity cost maintenance scheduling framework for a fleet of ships: A case study
O.E Charles-Owaba A.E Oluleye F.A Oyawale S.K OkeThe conventional method towards deriving schedule for a fleet of ships to minimize cost alone has the short-coming of not addressing the problem of operation revenue losses associated with delays during maintenance at ships dockyards. In this paper, a preventive mainten أکثرThe conventional method towards deriving schedule for a fleet of ships to minimize cost alone has the short-coming of not addressing the problem of operation revenue losses associated with delays during maintenance at ships dockyards. In this paper, a preventive maintenance schedule for a fleet of ships that incorporates op-portunity cost is presented. The idea is to assign a penalty cost to all idle periods that the ship spends at the dockyard. A version of the scheduling problem was defined as a transportation model of minimizing mainte-nance costs. Fixed maintenance duration and dockyard capacity were the two constraints of the formulation. Relevant data from a shipping firm owing 8 ships and a dockyard in Lagos with a maintenance capacity of three ships per month were collected over a 24-month period. The maintenance cost function was then formu-lated with the parameters estimated and the transportation tableau set up. The considered eight ships arrived at the dockyard between the 1st and 20th month, and were expected to spend between 2 to 5 months for preven-tive maintenance. The optimal schedule of the cost function resulted in ships 1 to 8 being idle for 74 months. The results of the study showed that to reduce the cost and delays, decisions for scheduling preventive main-tenance of a fleet of ships should be based on opportunity cost. تفاصيل المقالة -
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146 - Flexible resource management and its effect on project cost and duration
Desta A. Hailemariam Xiaojun Shan Sung H. Chung Mohammad T. Khasawneh William Lukesh Angela Park Adam Rose Denis C . Pinha Rashpal S. AhluwaliaIn practice, most projects result in cost overruns and schedule slippage due to poor resource management. This paper presents an approach that aims at reducing project duration and costs by empowering project managers to assess different scenarios. The proposed approach أکثرIn practice, most projects result in cost overruns and schedule slippage due to poor resource management. This paper presents an approach that aims at reducing project duration and costs by empowering project managers to assess different scenarios. The proposed approach addresses combinatorial modes for tasks, multi-skilled resources, and multiple calendars for resources. A case study reported in the literature is presented to demonstrate the capabilities of this method. As for practical implications, this approach enhances the decision-making process which results in improved solutions in terms of total project duration and cost. From an academic viewpoint, this paper adds empirical evidence to enrich the existing literature, as it highlights relevant issues to model properly the complexity of real-life projects. تفاصيل المقالة -
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147 - Role of batch size in scheduling optimization of flexible manufacturing system using genetic algorithm
Muhammad Umair Akhtar Muhammad Huzaifa Raza Muhammad ShafiqFlexible manufacturing system (FMS) readily addresses the dynamic needs of the customers in terms of variety and quality. At present, there is a need to produce a wide range of quality products in limited time span. On-time delivery of customers’ orders is critica أکثرFlexible manufacturing system (FMS) readily addresses the dynamic needs of the customers in terms of variety and quality. At present, there is a need to produce a wide range of quality products in limited time span. On-time delivery of customers’ orders is critical in make-to-order (MTO) manufacturing systems. The completion time of the orders depends on several factors including arrival rate, variability, and batch size, to name a few. Among those, batch size is a significant construct for effective scheduling of an FMS, as it directly affects completion time. On the other hand, constant batch size makes MTO less responsive to customers’ demands. In this paper, an FMS scheduling problem with n jobs and m machines is studied to minimize lateness in meeting due dates, with focus on the impact of batch size. The effect of batch size on completion time of the orders is investigated under following strategies: (1) constant batch size, (2) minimum part set, and (3) optimal batch size. A mathematical model is developed to optimize batch size considering completion time, lateness penalties and setup times. Scheduling of an FMS is not only a combinatorial optimization problem but also NP-hard problem. Suitable solutions of such problems through exact methods are difficult. Hence, a meta-heuristic Genetic algorithm is used to optimize scheduling of the FMS. تفاصيل المقالة -
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148 - Modeling and solving multi-skilled resource-constrained project scheduling problem with calendars in fuzzy condition
Sama Ahmadpour Vahidreza GhezavatiIn this study, we aim to present a new model for the resource-constrained project scheduling problem (RCPSP) considering a working calendar for project members and determined the skill factor of any member using the efficiency concept. For this purpose, the recyclable r أکثرIn this study, we aim to present a new model for the resource-constrained project scheduling problem (RCPSP) considering a working calendar for project members and determined the skill factor of any member using the efficiency concept. For this purpose, the recyclable resources are staff resources where any person with multiple skills can meet the required skills of activities in a given time. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. The proposed mathematical programming model optimizes the allocation of limited resources to project activities for scheduling purposes in an essential activity in the real condition of scheduling problems. Moreover, the proposed model can decrease the risk of deviation from scheduling by allocating members with higher skill factors to critical activities. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. Considering fuzzy conditions for the calendar of the project and multi-skill operators are firstly considered in this paper. Also, the recyclable resources are staff resources which are being considered for the model concurrently in response to the risks of availability to resources and delay in completing the project under uncertainty. The results derived from the model solved by CPLEX indicated a decreased need for employment and shortened project completion duration. Assuming the uncertainty of available resource capacity at any time, the results obtained from the fuzzy model for the value of objective function were evaluated under the influence of the resource calendar and showed the benefits. Effect of the multi-skill members with calendar constraints on the model is tested, and the advantages are determined. تفاصيل المقالة -
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149 - An integrated approach for scheduling flexible job-shop using teaching–learning-based optimization method
Raviteja Buddala Siba Sankar MahapatraIn this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There أکثرIn this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There are two sub problems in FJSP. They are routing problem and sequencing problem. If both the sub problems are solved simultaneously, then the FJSP comes under integrated approach. Otherwise, it becomes a hierarchical approach. Very less research has been done in the past on FJSP problem as it is an NP-hard (non-deterministic polynomial time hard) problem and very difficult to solve till date. Further, very less focus has been given to solve the FJSP using an integrated approach. So an attempt has been made to solve FJSP based on integrated approach using TLBO. Teaching–learning-based optimization is a meta-heuristic algorithm which does not have any algorithm-specific parameters that are to be tuned in comparison to other meta-heuristics. Therefore, it can be considered as an efficient algorithm. As best student of the class is considered as teacher, after few iterations all the students learn and reach the same knowledge level, due to which there is a loss in diversity in the population. So, like many meta-heuristics, TLBO also has a tendency to get trapped at the local optimum. To avoid this limitation, a new local search technique followed by a mutation strategy (from genetic algorithm) is incorporated to TLBO to improve the quality of the solution and to maintain diversity, respectively, in the population. Tests have been carried out on all Kacem’s instances and Brandimarte's data instances to calculate makespan. Results show that TLBO outperformed many other algorithms and can be a competitive method for solving the FJSP. تفاصيل المقالة -
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150 - Scheduling of undergraduate thesis examination: a case study in Industrial Engineering Department of Universitas Sebelas Maret
Cucuk Nur Rosyidi Endah Budiningsih Wakhid Ahmad JauhariUndergraduate thesis examination in Industrial Engineering Department of Universitas Sebelas Maret conducted through two stages, namely intermediate and final examination. Currently, the scheduling process of such examinations is done by the undergraduate thesis coordin أکثرUndergraduate thesis examination in Industrial Engineering Department of Universitas Sebelas Maret conducted through two stages, namely intermediate and final examination. Currently, the scheduling process of such examinations is done by the undergraduate thesis coordinator manually without certain systematic method or approach. In this paper, we develop an optimization model for the examinations scheduling considering several factors, namely the number of lecturers that must attend the examinations, the availability of rooms for examinations, the availability of each lecturer, and the assignment distributions. The model uses integer programming approach. Two performance criteria are used in the model, namely the difference between the number of each lecturer’s assignment with the average number of lecturer assignments and the number of penalties from the assignment of lecturers on certain time slot. The developed model is able to solve the scheduling problem more efficiently than manual scheduling done by thesis coordinator. The optimal solutions from the optimization model show a total difference in the assignment of lecturer with an average of 29.6 and a penalty of 0. تفاصيل المقالة -
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151 - A TCSC Control Based on Stabilizing Delay Effect for Inter-Area Oscillation Damping in a Power System with Time Delay
Yasaman Yardani Sefidi Rasoul Asghari Babak Mozafari Mohammad Salay NaderiAs opposed to the existing approaches which recognize communication network time delays, when they are introduced into the feedback signals, as a main cause of instability or poor performance in power system wide-area damping controller (WADC), this paper shows that if أکثرAs opposed to the existing approaches which recognize communication network time delays, when they are introduced into the feedback signals, as a main cause of instability or poor performance in power system wide-area damping controller (WADC), this paper shows that if time delay in feedback loops is properly determined, the WADC performance to damp out inter-area oscillations will be improved. In other words, in situations where it is not easy to design and implement the WADC for Flexible AC Transmission Systems (FACTS) devices without delay, in order to effectively compensate the delay, in this paper, a new Wide-Area Damping Controller Delay Effect (WADCDE) is designed. First the model of power system with delay as a design parameter is established. Then, the WADCDE based on objective function of the rightmost real part of eigenvalues is designed and the sufficient condition about stability of the closed-loop system is given. A four-machine power system for numerical simulations has been used to evaluate the accuracy of the proposed control function and the feasibility study. The simulation results showed that the controller designed in a wide range of delay feedback reduces the oscillation of power system without restricting TCSC operation. تفاصيل المقالة -
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152 - Joint Coordination of Wind Farms and Pumped Storage Plants in Generation Scheduling Using Modified Particle Swarm Optimization with Bacteria Foraging Concept
Hassan SiahkaliIncreasing penetration of renewable energy resources, especially wind power in power system operation, has some technical and economic effects because of the variable and uncertain nature of these resources. Therefore, it is very important for system operators to consid أکثرIncreasing penetration of renewable energy resources, especially wind power in power system operation, has some technical and economic effects because of the variable and uncertain nature of these resources. Therefore, it is very important for system operators to consider these behaviors necessary to solve the problem in this regard, especially generation scheduling problem. One of the most important strategies to increase the benefit of power system operation is to manage and control of wind power generation using pumped storage plants. A pumped storage plant can be used to provide added value to a wind farm to manage power output uncertainties. This paper presents a new approach for solving the weekly generation scheduling including wind farms and pumped storage plants. The hybrid PSO mechanism is suggested to solve this scheduling problem based on implementation of bacterial foraging concepts. The proposed PSO is applied to two test systems (which are included two wind farms and one pumped storage plant) and the results of this modified PSO are compared with the conventional PSO. Evaluation of the results of these test systems’ solutions show that better optimal schedules are obtained. تفاصيل المقالة -
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153 - Optimal Scheduling of a Renewable-based Micro Grid Considering Reliability Effect
Amir Ghaedi Reza Sedaghati Mehrdad MahmoudianIn the microgrids, it can be used from the renewable energy resources (RERs) such as photovolta-ic panels, wind turbines, wave energy converters and current type tidal turbines to reduce the greenhouse gas (GHG) emission arisen from fossil fuel-based generation units. H أکثرIn the microgrids, it can be used from the renewable energy resources (RERs) such as photovolta-ic panels, wind turbines, wave energy converters and current type tidal turbines to reduce the greenhouse gas (GHG) emission arisen from fossil fuel-based generation units. However, the generated electrical power of these RERs are dependent on the wave height and wave period, solar radiation, the wind speed, and the tidal current speed. Due to the wide variation in the RERs, the generated electrical power of these generation units changes a lot and so, to supply the local load in the isolated microgrid, the conventional generation units and the energy storage sys-tems (ESSs) can be utilized. In this paper, optimal scheduling of a microgrid containing conven-tional generation units, ESS and RERs including wind turbines, photovoltaic panels, current type tidal turbines and wave energy converters is performed to determine the generated power of each generation unit provided that the cost function is minimum. In the cost function, the operation cost of the generation units based on fossil fuel and the penalty cost associated to the load cur-tailment as the reliability cost are considered and using of the particle swarm optimization (PSO) algorithm, the cost function is minimized. To study the capability and effectiveness of the pre-sented approach, the numerical results associated to the optimal scheduling of a microgrid con-taining battery, RERs, and conventional units are presented. تفاصيل المقالة -
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154 - زمانبندی بهینه سرمایه‌گذار، تأمین مالی بدهی و مقیاس سرمایه‌گذاری بر مبنای تئوری چشم‌انداز The Optimal Timing of Capital Investment, Financing and Financing
نصیبه ولی زاده جواد رمضانی مهدی خلیل پورهدف این مقاله بررسی زمانبندی بهینه سرمایه‌گذار، تأمین مالی بدهی و مقیاس سرمایه‌گذاری میباشد. جامعه آماری این تحقیق شرکت‌های بورس اوراق بهادار تهران می باشد که تعداد 100 شرکت به عنوان نمونه در نظر گرفته میشود. تعداد 220 نفر از مدیران شرکت‌های فوق اقدام به پاسخگویی به أکثرهدف این مقاله بررسی زمانبندی بهینه سرمایه‌گذار، تأمین مالی بدهی و مقیاس سرمایه‌گذاری میباشد. جامعه آماری این تحقیق شرکت‌های بورس اوراق بهادار تهران می باشد که تعداد 100 شرکت به عنوان نمونه در نظر گرفته میشود. تعداد 220 نفر از مدیران شرکت‌های فوق اقدام به پاسخگویی به سؤالات پرسشنامه کردند. تحقیق حاضر در زمره تحقیقات کاربردی قرار دارد و از نظر روش، تحقیق توصیفی از نوع پیمایشی میباشد. در ادامه با استفاده از رویکرد حداقل مجذورات جزئی روابط متغیرهای تحقیق و مدل اصلی تحقیق بررسی‌شده است. داده‌های خام به‌دست‌آمده از جامعه آماری با استفاده از تکنیک‌های آماری مورد تجزیه‌وتحلیل و پس از پردازش به شکل اطلاعات ارائه‌شده است. نتایج نشان داد بین زمانبندی بهینه سرمایه‌گذار و کمک نقدی رابطه‌ی معناداری وجود دارد. بین تأمین مالی بدهی و کمک نقدی رابطه‌ی معناداری وجود دارد. بین مقیاس سرمایه‌گذاری و کمک نقدی رابطه‌ی معناداری وجود دارد.The Optimal Timing of Capital Investment,Financing and FinancingNasibeh ValizadehJavad RamezaniMehdi Khalil poorThe purpose of this paper is to investigate the optimal timing of capital investment, financing and financing. The statistical population of this research is Tehran Stock Exchange firms. The number of firms listed as the sample is considered. The respondents were asked to answer the questionnaire. This research is among applied research and in terms of method, it is a descriptive study of survey type. Then, using partial least squares approach, the relationship between research variables and main model of research is studied. The raw data obtained from the statistical society were analyzed using appropriate statistical techniques and smart pls software the results showed that there is a significant relationship between optimal operating time and cash assistance. There is a significant relationship between debt financing and cash assistance. There is a significant relationship between investment and cash flow. تفاصيل المقالة -
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155 - Optimizing Operation Scheduling in a Microgrid Considering Probabilistic Uncertainty and Demand Response Using Social Spider Algorithm
Amir Mortazi Seyedamin Saeed Hamidreza AkbariThe production of electrical energy from renewable sources has become an efficient solution to deal with the lack of fossil fuels, and prevent the emission of greenhouse gases and global warming. Due to the existence of different loads in terms of feeding priority, cons أکثرThe production of electrical energy from renewable sources has become an efficient solution to deal with the lack of fossil fuels, and prevent the emission of greenhouse gases and global warming. Due to the existence of different loads in terms of feeding priority, consumers can help the microgrid control center in optimizing the use of the microgrid and supplying energy to critical loads by providing the amount of load that can be interrupted or moved at different prices. Consumer pricing can reduce operating costs, especially when market prices are high. At the same time, with this method, consumers can economize on unimportant loads. In this paper, the effect of consumer pricing on the use of microgrids is analyzed considering the types of consumers and load priorities. The demand response program is achieved with the objective function of maximizing social welfare. on the other hand, the operation is principally concerned with flattening the load curve as much as possible. The flatter the load curve, the better the capacity installed in the network , and as a result, it postpones the development of generation and transmission. In this regard, an attempt is made to operate the microgrid in the presence of demand response, so that while increasing social welfare, the load curve is flat at an acceptable level. With these goals, the problem is formulated as a multi-objective objective function based on nonlinear programming GAMS optimization software used to solve the problem, and ε constraint will be used for multi-objective optimization. تفاصيل المقالة -
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156 - An Optimal Charge Framework Using Multivariate Copula for Day-ahead Scheduling of Electric Vehicle in Parking Lot Providing Power Markets
Mohamad Amin Gharibi Hamed Nafisi Hossein Askarian Abyaneh Amin HajizadehWith the increase of electric vehicles (EVs), forecasting and modeling charging load in parking lots and charging stations have become more important than ever. one of the most challenging problems in the optimal charging process is modeling EV owners' behavior. With es أکثرWith the increase of electric vehicles (EVs), forecasting and modeling charging load in parking lots and charging stations have become more important than ever. one of the most challenging problems in the optimal charging process is modeling EV owners' behavior. With estimating EV parameters charging stations can buy and sell energy in power markets. In this article, an optimal charging framework for electric vehicles in charging parking lots is presented, which reduces the cost of charging electric vehicles. In this study, real-time and day-ahead markets are considered simultaneously, for estimating EV's behavior the copula distribution is used as a more accurate distribution to model the electric vehicles data. In the optimal charging process, V2G and G2V processes and battery degradation are also considered. The simulation results show that by accurately modeling the behavior of EVs, the parking lot can participate in both markets and perform the optimal charging process and pay less than other ways. تفاصيل المقالة -
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157 - Optimal Placement and Scheduling of Switched Capacitor Banks Using Multi-Objective Hybrid Optimization Algorithm under Load Uncertainty Conditions
Ehsan AkbariA straightforward and affordable way to improve the power factor and account for reactive power (RP) in the distribution network (DN) is to employ switched capacitor banks (SCBs). The optimal placement of these capacitors helps to reduce costs and power losses in the ne أکثرA straightforward and affordable way to improve the power factor and account for reactive power (RP) in the distribution network (DN) is to employ switched capacitor banks (SCBs). The optimal placement of these capacitors helps to reduce costs and power losses in the network. This essay offers a hybrid algorithm by combining the Harris Hawks Optimization algorithm (HHO) and the Non-dominated Sorting Genetic Algorithm Type 2 (NSGA-II) to arrange the switched capacitors (SCs) in the DN in the best possible location and scheduling. Power plant active and reactive power (ARP) generation, capacitor bank (CB) capital expenditure (CapEx)and maintenance costs, ARP losses in DN, and switching costs of SC are all factored into the proposed objective function. Furthermore, the load uncertainty in this study is modeled using the normal distribution function. Finally, the proposed optimization problem is implemented on IEEE standard 33-bus networks, and the performance of the suggested hybrid approach is compared with other commonly used multi-objective optimization algorithms. The simulation results show the higher performance of the proposed algorithm in terms of convergence speed and the objective function value. تفاصيل المقالة -
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158 - Synchronizing of Smart Homes in Microgrids using Whale Optimization Algorithm
Farhad Nourozi Navid Ghardash khaniThe household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model أکثرThe household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model based on the time of usage pricing planning with renewable energy systems is proposed to use the energy more efficiently. The new meta-heuristic whale optimization algorithm (WOA) and the common meta-heuristic of particle swarm optimization (PSO) are used to achieve that. To improve the performance, a mapping chaos theory (CWOA) is proposed. Also, an independent solar energy source is used as a support of the microgrid to achieve a better performance. It is concluded that the energy saving achieved by the proposed algorithm is able to decrease the electricity bill by about 40-50% rather than the WOA and PSO methods. The proposed system is simulated in MATLAB environment. تفاصيل المقالة -
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159 - A Swarm-based Scheduling Algorithm for Lifetime Improvement of Visual Sensor Networks
Mir Gholamreza Mortazavi Mirsaeid Hosseini Shirvani Arash Dana Mahmood FathyVisual sensor networks (VSNs) apply directional sensors that can be configured only in one direction and also can be set in one of the possible observing ranges. In this battery-resource-limited environment, battery management and network lifetime expansion are still im أکثرVisual sensor networks (VSNs) apply directional sensors that can be configured only in one direction and also can be set in one of the possible observing ranges. In this battery-resource-limited environment, battery management and network lifetime expansion are still important challenges. The target coverage problem in such networks, in which all of the specified targets must be continuously observed and monitored by administrators is formulated as an integer linear programming problem (ILP) that is an NP-Hard problem. Although several approaches have been presented in the literature to solve the aforementioned problem, the majority of them suffer from getting stuck in the local trap and low exploration in search space. To address the issue, a discrete cuckoo-search optimization algorithm (DCSA) is extended to solve this combinatorial problem. The discrete operator of the proposed algorithm is designed in such a way that explore search space efficiently and lead to balancing in the local and global search process. The proposed algorithm was examined in different conducted scenarios. The returned results of simulations of numerous scenarios show the dominance of the proposed algorithm in comparison with other existing approaches in terms of network lifetime maximization. In other words, the proposed DCSA has 19.75% and 13.75% improvement in terms of network average lifetime expansion against HMNLAR and GA-based approaches respectively in all scenarios. تفاصيل المقالة -
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160 - Flexible Scheduling of Active Distribution Networks for Market Participation with Considering DGs Availability
Milad Hoseinpour M.-R HaghifamThe availability of sufficient and economic online capacity to support the network while encountering disturbances and failures leading to supply and demand imbalance has a crucial role in today distribution networks with high share of Distributed Energy Resources (DERs أکثرThe availability of sufficient and economic online capacity to support the network while encountering disturbances and failures leading to supply and demand imbalance has a crucial role in today distribution networks with high share of Distributed Energy Resources (DERs), especially Renewable Energy Resources (RESs). This paper proposes a two-stage decision making framework for the Distribution Management System (DMS) to flexibly optimize the day-ahead schedule of DERs and market participation of distribution networks under uncertainties, imposed by DGs outage and wind generators. The uncertainties are modeled via scenarios and convolved with each other, and then the joint scenario set is applied in the proposed two-stage programming model. Also the role of network constraints on DMS decisions are seen via a linearized AC power flow model and finally the resulted proposed framework is based on mixed-integer-linear programming (MILP) layout solved by CPLEX 12.6. To examine the effectiveness of the proposed framework, it is used for decision making of DERs scheduling and market participation strategy of a test distribution network. تفاصيل المقالة -
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161 - MODELLING AND ANALYSIS OF A DISCRETE-TIME PRIORITY QUEUING COMPUTER NETWORK WITH PRIORITY JUMPS USING PROBABILITY GENERATING FUNCTIONS
Deepak C. Pandey Arun K. PalPriority queues have a great importance in the study of computer communication networks in which different types of traffic require different quality of service standards. The discrete-time non-preemptive priority queuing model with priority jumps is proposed in this pa أکثرPriority queues have a great importance in the study of computer communication networks in which different types of traffic require different quality of service standards. The discrete-time non-preemptive priority queuing model with priority jumps is proposed in this paper. On the basis of probability generating functions mean system contents and mean queuing delay characteristics are obtained. The effect of jumping mechanism is analysed which clearly shows that the queuing system provides better results when the fraction of class-1 arrivals in the overall traffic mix is small. تفاصيل المقالة -
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162 - A SIMPLIFIED LAGRANGIAN MULTIPLIER APPROACH FOR FIXED HEAD SHORT-TERM HYDROTHERMAL SCHEDULING
S. Kavitha Nirmala P.RatchagarThis paper presents a simplifiedlagrangian multiplier based algorithm to solve the fixed head hydrothermalscheduling problem. In fixed head hydrothermal scheduling problem, waterdischarge rate is modeled as quadratic function of hydropower generation andfuel cost is mod أکثرThis paper presents a simplifiedlagrangian multiplier based algorithm to solve the fixed head hydrothermalscheduling problem. In fixed head hydrothermal scheduling problem, waterdischarge rate is modeled as quadratic function of hydropower generation andfuel cost is modeled as quadratic function of thermal power generation. Thepower output of each hydro unit varies with the rate of water dischargedthrough the turbines. It is assumed that hydro plants alone are not sufficientto supply all the load demands during the scheduling horizon. In hydroscheduling, the specified total volume of water should be optimally dischargedthroughout the scheduling period. A novel mathematical approach has been developedto determine the optimal hydro and thermal power generation so as to minimizethe fuel cost of thermal units. The performance of the proposed method isdemonstrated with three test systems. The test results reveal that the proposedmethod provides optimal solution which satisfies the various system constraintsof fixed head hydrothermal scheduling problem. تفاصيل المقالة -
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163 - Irrigation Water Volume and Water Efficiency of Walnut Orchards in As-Suwayda, Syria
Hussam Abdullah Abbas Ammar Dham Hamza Radhi Zainab Hussein Adhub Majeed M. Abid Noora M. Hameed Hanan Askar HussnyIn recent years, the demand for walnuts has increased due to their recognition as a nutritious food and a versatile ingredient in cooking and baking. As a result, walnut production has become a significant industry in many countries, providing income and employment oppo أکثرIn recent years, the demand for walnuts has increased due to their recognition as a nutritious food and a versatile ingredient in cooking and baking. As a result, walnut production has become a significant industry in many countries, providing income and employment opportunities for growers and processors. Despite the fact that one of the most important products in the world and Syria is walnuts, there has been little research on irrigation and, in particular, water productivity. Therefore, the purpose of this study is to examine the irrigation status and water productivity in several walnut orchards in As-Suwayda province, which is a significant production area for this product. In the course of this research, water productivity, irrigation water volume, and the crop performance of walnut orchards in three of the most important producing locations of this commodity in the province of As-Suwayda (Sweida) were evaluated and compared. Drip irrigation and surface irrigation methods were investigated. The t-test was used to compare irrigation water levels in orchards with gross water requirements. Drip irrigation systems in orchards save around 1700 m3 ha-1 of irrigation water, reduce yields by an average of 145 kg ha-1, and boost water productivity by roughly 0.02 kg m3, according to the findings, but none of these differences were statistically significant at the 5% level. In general, there was not a discernible difference found between drip and surface irrigation systems in terms of performance values, amount of water applied, or water productivity. تفاصيل المقالة -
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164 - A TOPSIS-Based Improved Weighting Approach With Evolutionary Computation
Mithat Zeydan Murat Güngör Burak UrazelAlthough optimization of weighted objectives is ubiquitous in production scheduling, the literature concerning the determination of weights used in these objectives is scarce. Authors usually suppose that weights are given in advance, and focus on the solution methods f أکثرAlthough optimization of weighted objectives is ubiquitous in production scheduling, the literature concerning the determination of weights used in these objectives is scarce. Authors usually suppose that weights are given in advance, and focus on the solution methods for the specific problem at hand. However, weights directly settle the class of optimal solutions, and are of utmost importance in any practical scheduling problem. In this study, we propose a new weighting approach for single machine scheduling problems. First, factor weights to be used in customer evaluation are found by solving a nonlinear optimization problem using the covariance matrix adaptation evolutionary strategy (CMAES) under fuzzy environment that takes a pairwise comparison matrix as input. Next, customers are sorted using the technique for order of preference by similarity to ideal solution (TOPSIS) by means of which job weights are obtained. Finally, taking these weights as an input, a total weighted tardiness minimization problem is solved by using mixed-integer linear programming to find the best job sequence. This combined methodology may help companies make robust schedules not based purely on subjective judgment, find the best compromise between customer satisfaction and business needs, and thereby ensure profitability in the long run. تفاصيل المقالة
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