Simulated Annealing

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1 - بهره‌وری نیروی انسانی با رویکرد چرخش شغلی با استفاده از الگوریتم فرا ابتکاری فاخته
نسرین جمالی منفرد سید احمد شیبت الحمدی

این تحقیق به دنبال یافتن مدل مناسبی و حل آن جهت حل مشکل چرخش شغلی در یک شرکت می‌باشد که به منظور کاهش هزینه و حداقل سازی حجم کار صورت پذیرفته است، تا بتوان با حداقل کردن هزینه بهره وری سازمان را افزایش دهد که با توجه به مدل سازی انجام شده از شرایط شرکت پیکسل و بررسی مور أکثر

این تحقیق به دنبال یافتن مدل مناسبی و حل آن جهت حل مشکل چرخش شغلی در یک شرکت می‌باشد که به منظور کاهش هزینه و حداقل سازی حجم کار صورت پذیرفته است، تا بتوان با حداقل کردن هزینه بهره وری سازمان را افزایش دهد که با توجه به مدل سازی انجام شده از شرایط شرکت پیکسل و بررسی موردی آن با لحاظ محدودیت‌های پیشرو انجام پذیرفت نشان داده می‌شود که پیچیدگی این مساله از نوع NP سخت است و در نتیجه استفاده از روشهای دقیق برای حل مساله در زمان معقول امکان پذیر نیست. مدل برنامه ریزی بر اساس یک مسئله زمانبندی نیروی انسانی که نیاز به کارکرد 12 ساعت از روز و 7 روز هفته در یک محیط عملیاتی است به طوری که وضعیت کارگران با این شرایط محاسبه شده اند.در این تحقیق تلاش بر حدقل رسانیدن هزینه حجم کاری (بار کاری) W در کل برنامه برای هر یک از کارگر‌ها که خدمات ارائه می‌دهند در 24 ساعت روز و 7 روز هفته انجام می‌گیرد.مفروضات مدل پیشنهادی عبارت است از اینکه سازمان 12 ساعت در روز کار می‌کند، افق برنامه ریزی در مدل تحقیق) 7-r) روز از هفته می‌باشد، هر کارگر در هفته r روز شامل off-day می‌شود، یک شیفت کاری به صورت، زمان شروع و طول شیفت، تعریف می‌گردد، شیفت کاری تمام وقت مجاز می‌باشد، در برنامه m کار با هزینه کارگری (حجم کاری) متفاوت دارد که با توجه به روز و هفته قابلیت جابه جایی دارد، همه کارگران دارای شرایط یکسان کاری می‌باشند. برای حل این مساله از یک الگوریتم تکاملی استفاده خواهد شد که در اینجا الگوریتم فاخته انتخاب شده است که در نرم افزار متلب کد نویسی شده و به منظور حل آن از الگوریتم فاخته استفاده شد. و نتایج آن با الگوریتم شبیه سازی تبرید مقایسه گردید نتایج بدست آمده بیانگر آن بوده است که الگوریتم فاخته بهینه ترین جواب جهت برازش مدل را به ما معرفی نموده است. تفاصيل المقالة

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2 - پیش بینی جریان آبراهه ای با استفاده از مدل های هیبریدی هوشمند در مقیاس ماهانه (مطالعه موردی: رودخانه زرین رود)
بابک محمدی روزبه موذن زاده

10.22034/jest.2020.24315.3331

زمینه و هدف: انتخاب ورودی‌های مناسب برای مدل‌های هوشمند از اهمیت بسزایی برخوردار است زیرا باعث کاهش هزینه و صرفه‌جویی در وقت و افزایش دقت و کارایی مدل‌ها می‌شود. هدف از پژوهش حاضر،کاربرد آنتروپی شانون برای انتخاب ترکیب بهینه متغیرهای ورودی در شبیه سازی دبی ماهانه توسط پ أکثر

زمینه و هدف: انتخاب ورودی‌های مناسب برای مدل‌های هوشمند از اهمیت بسزایی برخوردار است زیرا باعث کاهش هزینه و صرفه‌جویی در وقت و افزایش دقت و کارایی مدل‌ها می‌شود. هدف از پژوهش حاضر،کاربرد آنتروپی شانون برای انتخاب ترکیب بهینه متغیرهای ورودی در شبیه سازی دبی ماهانه توسط پارامترهای هواشناسی می‌باشد. روش بررسی: در این مطالعه داده های هواشناسی و سری زمانی ماهانه دبی رودخانه زرین رود (ایستگاه صفاخانه) واقع در آذربایجان- شرقی در دوره زمانی 1336تا1394 مورد استفاده قرارگرفت. پارامترهای هواشناسی و ماه از سال به‌عنوان ورودی در روش آنتروپی به منظور تعیین ترکیب موثر در نظر گرفته شد. یافته ها: نتایج آنتروپی شانون نشان داد که پارامترهای بارش ، ماه از سال و دما ، نتایج بهتری را برای مدل‌سازی ارایه می‌دهد. شبیه‌سازی با استفاده از مدل های هیبرید هوشمند الگوریتم هیبریدی ازدحام ذرات و الگوریتم هیبریدی شبیه سازی تبرید انجام گرفت.کارایی مدل‌ها با استفاده از معیار ضریب تبیین ،ریشه جذر میانگین خطا وشاخص پراکندگی محاسبه گردید. بحث و نتیجه گیری: نتایج نشان داد از میان این مدل ها با ساختار ورودی‌های یکسان، مدل الگوریتم هیبریدی شبیه سازی تبرید بر پایه ماشین بردار پشتیبان عملکرد بهتری برای شبیه‌سازی دبی جریان در مقایسه با سایر مدل های هیبریدی هوشمند داشته است. همچنین نتایج تحقیق نشان داد که روش آنتروپی در انتخاب بهترین ترکیب ورودی در مدل‌های هوشمند از کارایی خوبی برخوردار است. تفاصيل المقالة

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3 - پیش بینی شاخص بورس تهران با استفاده از سری زمانی فازی بر اساس تعریف نرخ بازده
فرید رادمهر ناصر شمس قارنه

در سالیان اخیر تحقیقات گسترده ای برروی مدل ها ی سری زمانی فازی انجام شده است اما در بسیاری از این تحقیقات، همواره فضای مسئله و بازه های مربوطه، بر اساس سطوح داده ها ی سری زمانی تعیین شده است. در این تحقیق با نگاهی جدید به تعیین فضای مسئله و استفاده از مفهوم نرخ بازده در أکثر

در سالیان اخیر تحقیقات گسترده ای برروی مدل ها ی سری زمانی فازی انجام شده است اما در بسیاری از این تحقیقات، همواره فضای مسئله و بازه های مربوطه، بر اساس سطوح داده ها ی سری زمانی تعیین شده است. در این تحقیق با نگاهی جدید به تعیین فضای مسئله و استفاده از مفهوم نرخ بازده در بازارهای مالی، نوع جدیدی از فضای مسئله بر اساس نرخ بازده برای کاربرد در بازار های مالی و پیش بینی سری های زمانی مالی ارائه شده است. یکی از مسائل دیگر در مدل های سری زمانی فازی که تاثیر به سزایی در عملکرد آنها دارد طول بازه های مورد استفاده و نحوه ی تقسیم بندی فضای مسئله می باشد که در این زمینه تحقیقات متنوعی انجام شده است اما نتایج حاصله تا کنون راضی کننده نیست. لذا در این تحقیق با استفاده از الگوریتم شبیه سازی تبرید سعی در برطرف نمودن ایرادات مطالعات قبلی برای تعیین بازه های مناسب شده است. حاصل تحقیق مدل RBFTS است. برای مقایسه عملکرد مدل ارائه شده و مدل های موجود در ادبیات، از دو مسئله ی بورس تایفکس و پذیرش دانشگاه آلاباما که به عنوان مرجع مقایسه ی این دسته از مدل ها هستند استفاده شده است. نتایج حاصله نشان دهنده ی برتری مدل های ارائه شده نسبت به مدل های پیشین است. در نهایت به عنوان مورد اجرایی، دو مدل نامبرده برروی شاخص بازار بورس تهران اجرا شده و نتایج تحلیل گردید. تفاصيل المقالة

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4 - A new multi-mode and multi-product hub covering problem‎: ‎A priority M/M/c queue ‎approach
S. Sedehzadeh&lrm; R. Tavakkoli-&lrm;Moghaddam&lrm;&lrm; F. Jolai&lrm;

One main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. This paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between أکثر

One main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. This paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. Indeed, the nature of products is considered different and hub capacity constraint is also applied. Due to the transport volume and related traffic, a new priority M/M/c queuing system is considered, in which products with high priority are selected for service ahead of those with low priority. The objectives of this model minimize the total transportation cost and total time. Besides, because of the computational complexity, a multi-objective parallel simulated annealing (MOPSA) algorithm is proposed and some computational experiments are provided to illustrate the efficiency of the presented model and proposed MOPSA algorithm. The performance of this algorithm is compared with two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy (PAES)&lrm;.&lrm; تفاصيل المقالة

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5 - A Multi-supplier Inventory Model with Permissible Delay in Payment and ‎Discount
M. Farhangi E. Mehdizadeh

&lrm;This paper proposes a multi-supplier multi-product inventory model in which the suppliers have unlimited production capacity, allow delayed payment, and offer either an all-unit or incremental discount. The retailer can delay payment until after they have sold all أکثر

&lrm;This paper proposes a multi-supplier multi-product inventory model in which the suppliers have unlimited production capacity, allow delayed payment, and offer either an all-unit or incremental discount. The retailer can delay payment until after they have sold all the units of the purchased product. The retailerâ€™s warehouse is limited, but the surplus can be stored in a rented warehouse at a higher holding cost. The demand over a finite planning horizon is known. This model aims to choose the best set of suppliers and also seeks to determine the economic order quantity allocated to each supplier. The model will be formulated as a mixed integer and nonlinear programming model which is NP-hard and will be solved by using genetic algorithm (GA), simulated annealing (SA) algorithm, and vibration damping optimization (VDO) algorithm. Finally, the performance of the algorithms will be &lrm;compared.&lrm; تفاصيل المقالة

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6 - پیش‌بینی ریسک پروژه‌های نرم‌افزار توسط الگوریتم بهینه‌سازی ملخ و یادگیری ماشین
بهار احمدی هادی خسروی فارسانی تقی جاودانی گندمانی

توسعه نرم‌افزار را می‌توان فعالیتی دانست که از انواع پیشرفت‌های فناورانه استفاده می‌کند و نیاز به دانش بالایی دارد. به همین دلیل، هر پروژه توسعه نرم‌افزاری حاوی عناصر عدم قطعیت است که به‌عنوان ریسک پروژه شناخته می‌شود. موفقیت یک پروژه توسعه نرم‌افزار به‌شدت به میزان ریس أکثر

توسعه نرم‌افزار را می‌توان فعالیتی دانست که از انواع پیشرفت‌های فناورانه استفاده می‌کند و نیاز به دانش بالایی دارد. به همین دلیل، هر پروژه توسعه نرم‌افزاری حاوی عناصر عدم قطعیت است که به‌عنوان ریسک پروژه شناخته می‌شود. موفقیت یک پروژه توسعه نرم‌افزار به‌شدت به میزان ریسک مربوط به هر فعالیت پروژه بستگی دارد. لذا، به‌عنوان یک مدیر پروژه، آگاهی از خطرات کافی نیست. جهت دستیابی به یک نتیجه موفق، یک مدیر پروژه باید بتواند تمام ریسک‌های اصلی را شناسایی، سپس ارزیابی، اولویت‌بندی و درنهایت مدیریت کند. مدیریت ریسک بر شناسایی ریسک‌ها و درمان مناسب با آن‌ها تمرکز دارد. پروژه‌های نرم‌افزاری دارای ریسک‌های فردی یا کلی هستند. برخی از این ریسک‌ها به یک فعالیت خاص و برخی دیگر به پروژه مرتبط است. معمولاً ریسک‌ها ابتدا شناسایی‌شده و با فعالیت‌های پروژه مرتبط می‌شوند. تعیین چگونگی رفتار افراد برای دستیابی به اهداف فعالیت استراتژیک برای شناسایی خطرات است. استفاده از الگوریتم‌ها و فن‌های مختلف برای شناسایی ریسک‌های نرم‌افزاری همواره موردتوجه متخصصین بوده است. هدف این مطالعه، پیش‌بینی ریسک‌های پروژه‌های نرم‌افزاری به کمک الگوریتم بهینه‌سازی ملخ می‌باشد. در این روش انتخاب ویژگی و کاهش آن‌ توسط الگوریتم بهینه‌سازی ملخ انجام می‌شود و برای طبقه‌بندی ریسک و ویژگی‌ها از روش‌های طبقه‌بندی ماشین بردار استفاده می‌شود. تفاصيل المقالة

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7 - Meta-heuristic methods to solve the problem of subway station facilities in urban management
Mehdi Fazli somayyeh faraji amoogin

We consider several location inventory optimization models for the supply chain configuration of subway facilities. It includes several distribution centers and several retailers. Customer demand and redelivery time are considered random. The goal is to find the optimal أکثر

We consider several location inventory optimization models for the supply chain configuration of subway facilities. It includes several distribution centers and several retailers. Customer demand and redelivery time are considered random. The goal is to find the optimal locations for facilities and their inventory policy simultaneously. For this purpose, a two-phase approach based on queuing theory and stochastic optimization was developed. Today, meta-heuristic methods are often used to solve optimization problems such as facility design. in this study; The design of different units, stores, and rooms of a real large-scale subway was organized using three meta-heuristic methods: Migratory Bird Optimization (MBO), Taboo Search (TS), and Simulated Simulation (SA). The results were compared with the existing subway design. As a result, the meta-heuristic methods of MBO and SA have provided the best results that improve the efficiency of the existing subway design to an acceptable level. تفاصيل المقالة

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8 - قیمت گذاری کاهشی محصولات فسادپذیر در شرایط وابستگی تقاضا به قیمت و موجودی در معرض نمایش
Ameneh Jeihouni Hossein Safari Ameneh Jeihouni Mohammad Reza Sadeghi Moghadam Farzad Bahrami

10.30495/imj.2021.682760

در این مقاله برای دستیابی به حداکثر سود حاصل از فروش محصولات فسادپذیر سیاست کاهش قیمت یا تخفیف به کار گرفته شده است. به دلیل اینکه محصولات فسادپذیر پس از یک بازه زمانی دچار افت کیفیت شده و فساد در آنها شکل می‌گیرد ، بنابراین نزد مشتری از جذابیت لازم برخوردار نیستند و تق أکثر

در این مقاله برای دستیابی به حداکثر سود حاصل از فروش محصولات فسادپذیر سیاست کاهش قیمت یا تخفیف به کار گرفته شده است. به دلیل اینکه محصولات فسادپذیر پس از یک بازه زمانی دچار افت کیفیت شده و فساد در آنها شکل می‌گیرد ، بنابراین نزد مشتری از جذابیت لازم برخوردار نیستند و تقاضا برای خرید این محصولات کاهش می یابد، با سیاست کاهش قیمت می توان تقاضا را افزایش داد همچنین با بالارفتن میزان فروش، ضایعات نیز کاهش خواهد یافت و کاهش هزینه خواهیم داشت ؛بنابراین سود کل افزایش خواهد یافت. حال مسأله اینست که اگر تخفیف در زمان مناسب و مقدار بهینه ارائه نشود به هدف رسیدن به حداکثر سود نخواهیم رسید. لذا، در این مقاله به دنبال تعیین زمان بهینه تخفیف و مقدار بهینه تخفیف هستیم با هدف ماکزیمم کردن سود کل بنگاه مفروضات این مقاله تابع تقاضا وابسته به دو عامل قیمت فروش و موجودی در معرض نمایش، سطح موجودی نهایی غیر صفر و نرخ فساد ثابت می باشد. پس از حل مدل از رویکرد دقیق و مثال عددی، مثال با استفاده از الگوریتم ژنتیک، الگوریتم تبرید شبیه‌سازی‌شده حل شده و نتایج مقایسه شد و سپس تحلیل حساسیت پارامترهای اصلی سیستم انجام گردید. تفاصيل المقالة

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9 - بهینه سازی موقعیت برداشت نمونه های تکمیلی در منطقه سپاهان شهر با استفاده از ترکیب مطالعات زمین آماری و روش تبرید شبیه سازی شده
سعید سلطانی محمدی ملیحه عباس زاده اردشیر هزار خانی

بهینه سازی طرح نمونه برداری از موضوعات مهم و جذاب برای متخصصین زمین آمار و ژئوشیمیست هاست و تا به امروز روشهای متنوعی در زمینه بهینه سازی موقعیت برداشت نمونه ها (اولیه و تکمیلی)ارائه گردیده است.در این مقاله سعی شده است تا با استفاده از روش تبرید شبیه سازی شده،موقعیت برد أکثر

بهینه سازی طرح نمونه برداری از موضوعات مهم و جذاب برای متخصصین زمین آمار و ژئوشیمیست هاست و تا به امروز روشهای متنوعی در زمینه بهینه سازی موقعیت برداشت نمونه ها (اولیه و تکمیلی)ارائه گردیده است.در این مقاله سعی شده است تا با استفاده از روش تبرید شبیه سازی شده،موقعیت برداشت نمونه های تکمیلی در مطالعات زیست محیطی منطقه سپاهان شهر بهینه گردد.در منطقه سپاهان شهر علاوه بر عامل مجاورت با محدوده معدنی ایرانکوه(عامل آلاینده) بادهایی که جهت غالب وزش آنها در طول سال ،از سمت این محدوده معدنی به سمت دشت سپاهان شهر می باشد،احتمال آلوده شدن منطقه را افزایش داده است.با استفاده از واریانس تخمین به عنوان معیار عدم قطعیت تخمین ،روشی برای بهینه سازی نقاط نمونه برداری تکمیلی بر اساس اطلاعات حاصل از برداشتهای اولیه ارائه شد.کمینه سازی واریانس تخمین به عنوان تابع هدف تعریف شد که تابعی غیر خطی استو از آنجا که تعداد بسیار زیاد ترکیبات ممکن،استفاده از روشهای جستجوی جامع را برای حل این مساله غیر ممکن ساخته است،از روش فراحسی تبرید شبیه سازی شده برای حل مساله استفاده شد.برداشت نمونه های تکمیلی پیشنهادی از این روش منجر به کاهش واریانس تخمین میانگین منطقه از 0.34 به 0.22 خواهد شد،که بیشترین کاهش عدم قطعیت تخمینی است که می تواند در نتیجه برداشت این تعداد نمونه ایجاد شود.استفاده از این روش می تواند نقش به سزایی در کاهش هزینه های نمونه بردای و هدفمند نمودن آنها داشته باشد. تفاصيل المقالة

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10 - Improving Energy-Efficient Target Coverage in Visual Sensor Networks
Behrooz Shahrokhzadeh Mehdi Dehghan MohammadReza Shahrokhzadeh

Target 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 أکثر

Target 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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11 - An Integrated Model of Project Scheduling and Material Ordering: A Hybrid Simulated Annealing and Genetic Algorithm
Nima Zoraghi Amir Abbas Najafi سید تقی اخوان نیاکی

This 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 أکثر

This 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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12 - A Continuous Review inventory Control Model within Batch Arrival Queuing Framework: A Parameter-Tuned Imperialist Competitive Algorithm
Mohammad Alaghebandha Seyed Hamid Reza Pasandideh Vahid Hajipour

In this paper, a multi-product continues review inventory control problem within batch arrival queuing approach (MQr/M/1) is modeled to find the optimal quantities of maximum inventory. The objective function is to minimize summation of ordering, holding and shortage co أکثر

In this paper, a multi-product continues review inventory control problem within batch arrival queuing approach (MQr/M/1) is modeled to find the optimal quantities of maximum inventory. The objective function is to minimize summation of ordering, holding and shortage costs under warehouse space, service level, and expected lost-sales shortage cost constraints from retailer and warehouse viewpoints. Since the proposed model is Np-Hard, an efficient imperialist competitive algorithm (ICA) is proposed to solve the model. To justify proposed ICA, a simulated annealing algorithm has been utilized. In order to determine the best value of algorithms parameters that result in a better solution, a fine-tuning procedure is executed. Finally, the performance of the proposed ICA is analyzed using some numerical illustrations. تفاصيل المقالة

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13 - A Comparative Study of Four Evolutionary Algorithms for Economic and Economic-Statistical Designs of MEWMA Control Charts
سید تقی اخوان نیاکی مهدی Malaki محمد جواد ارشادی

The multivariate exponentially weighted moving average (MEWMA) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. The economic de أکثر

The multivariate exponentially weighted moving average (MEWMA) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. The economic design of MEWMA control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function and traditional linear constraints. The cost function in this model is a complex nonlinear function that formulates the cost of implementing the MEWMA chart economically. An economically designed MEWMA chart to possess desired statistical properties requires some additional statistical constraints to be an economic-statistical model. In this paper, the efficiency of some major evolutionary algorithms that are employed in economic and economic-stati stical design of a MEWMA control chart are discussed comparatively and the results are presented. Theinvestigated evolutionary algorithms are simulated annealing (SA), differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO), which are the most well known algorithms to solve complex combinatorial optimization problems. The major metrics to evaluate the algorithms are (i) the quality of the best solution obtained, (ii) the trends of responses in approaching the optimum value, (iii) the average objective-function-value in all trials, and (iv) the computer processing time to achieve the optimum value. The result of the investigation for the economic design shows that while GA is the most powerful algorithm, PSO is the second to the best, and then DE and SA come to the picture. For economic-statistical design, while PSO is the best and GA is the second to the best, DE and SA have similar performances. تفاصيل المقالة

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14 - The project portfolio selection and scheduling problem: mathematical model and algorithms
Bahman Naderi

This 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 أکثر

This 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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15 - A Honey Bee Algorithm To Solve Quadratic Assignment Problem
mohamad mirzazadeh غلام حسن شیردل behrooz masoumi

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in f أکثر

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first of all, we have been described exact methods and heuristics, which are able to solve QAP; then we have been applied a meta-heuristic algorithm for it. QAP is a difficult problem and is in NP-hard class, so we have been used honey bee mating optimization (HBMO) algorithm to solve it.This method is new and have been applied and improved NP-hard problems. It’s a hybrid algorithm from Honey-Bee Mating system, simulated annealing and genetic algorithm. تفاصيل المقالة

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16 - َA Multi-objective simulated annealing algorithm to solving flexible no-wait flowshop scheduling problems with transportation times
Bahman Naderi Hassan Sadeghi

This 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 أکثر

This 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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17 - A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers
Parviz Fattahi Parvaneh Samouei

10.22094/joie.2016.246

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number أکثر

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm. This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm تفاصيل المقالة

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18 - A simulated annealing algorithm to determine a group layout and production plan in a dynamic cellular manufacturing system
Reza KiA Nikbakhsh Javadian Reza Tavakkoli-Moghaddam

In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensiv أکثر

In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented model different from the previous studies. These include: 1) the variable number of cells, 2) machine depot keeping idle machines, and 3) integration of cell formation (CF), GL and PP decisions in a dynamic environment. The objective is to minimize the total costs (i.e., costs of intra-cell and inter-cell material handling, machine relocation, machine purchase, machine overhead, machine processing, forming cells, outsourcing and inventory holding). Two numerical examples are solved by the GAMS software to illustrate the results obtained by the incorporated features. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in compare to the GAMS software. The obtained results show that the quality of the solutions obtained by SA is entirely satisfactory in compare to GAMS software based on the objective value and computational time, especially for large-sized problems. تفاصيل المقالة

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19 - Machine scheduling for multitask machining
Saleh Yavari Ahmed Azab Mohammed Fazle Baki Mikel Alcelay Justin Britt

10.22094/joie.2020.1869865.1660

Multitasking 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 أکثر

Multitasking 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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20 - Three Hybrid Metaheuristic Algorithms for Stochastic Flexible Flow Shop Scheduling Problem with Preventive Maintenance and Budget Constraint
Sadigh Raissi Ramtin Rooeinfar Vahid Reza Ghezavati

10.22094/joie.2018.242.1532

Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job pr أکثر

Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fixed interval preventive maintenance (PM) and budget constraint are considered.PM activity is a crucial task to reduce the production efficiency. In the current research we focused on a scheduling problem which a job is processed at the upstream stage and all the downstream machines get busy or alternatively PM cost is significant, consequently the job waits inside the buffers and increases the associated holding cost. This paper proposes a new more realistic mathematical model which considers both the PM and holding cost of jobs inside the buffers in the stochastic flexible flow shop scheduling problem. The holding cost is controlled in the model via the budget constraint. In order to solve the proposedmodel, three hybrid metaheuristic algorithms are introduced. They include a couple of well-known metaheuristic algorithms which have efficient quality solutions in the literature. The two algorithms of them constructed byincorporationof the particle swarm optimization algorithm (PSO) and parallel simulated annealing (PSA) methods under different random generation policies. The third one enriched based on genetic algorithm (GA) with PSA. To evaluate the performance of the proposed algorithms, different numerical examples are presented. Computational experiments revealed that the proposed algorithms embedboth desirable accuracy and CPU time. Among them, the PSO-PSAП outperforms than other algorithms in terms of makespan and CPU time especially for large size problems. تفاصيل المقالة

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21 - A new multi-objective mathematical model for a Citrus supply chain network design: Metaheuristic algorithms
M.B. Fakhrzad F. Goodarzian

10.22094/joie.2020.570636.1571

Nowadays, the citrus supply chain has been motivated by both industrial practitioners and researchers due to several real-world applications. This study considers a four-echelon citrus supply chain, consisting of gardeners, distribution centers, citrus storage, and frui أکثر

Nowadays, the citrus supply chain has been motivated by both industrial practitioners and researchers due to several real-world applications. This study considers a four-echelon citrus supply chain, consisting of gardeners, distribution centers, citrus storage, and fruit market. A Mixed Integer Non-Linear Programming (MINLP) model is formulated, which seeks to minimize the total cost and maximize the profit of the Citrus supply chain network. Due to the complexity of the model when considering large-scale samples, two well-known meta-heuristic algorithms such as Ant Colony Optimization (ACO) and Simulated Annealing (SA) algorithms have been utilized. Additionally, a new multi-objective ACO algorithm based on a set of non-dominated solutions form the Pareto frontier developed to solve the mathematical model. An extensive comparison based on different measurements analyzed to find a performance solution for the developed problem in the three sizes (small, medium, and large-scale). Finally, the various outcomes of numerical experiments indicate that the MOACO algorithm is more reliable than other algorithms. تفاصيل المقالة

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22 - A New Hybrid Parallel Simulated Annealing Algorithm for Travelling Salesman Problem with Multiple Transporters
parham azimi Ramtin Rooeinfar Hani Pourvaziri

In today’s competitive transportation systems, passengers search to find traveling agencies that are able to serve them efficiently considering both traveling time and transportation costs. In this paper, we present a new model for the traveling salesman problem w أکثر

In today’s competitive transportation systems, passengers search to find traveling agencies that are able to serve them efficiently considering both traveling time and transportation costs. In this paper, we present a new model for the traveling salesman problem with multiple transporters (TSPMT). In the proposed model, which is more applicable than the traditional versions, each city has different transporting vehicles and the cost of travel through each city is dependent on the transporting vehicles type. The aim is to determine an optimal sequence of visited cities with minimum traveling times by available transporting vehicles within a limited budget. First, the mathematical model of TSPMT is presented. Next, since the problem is NP-hard, a new hybrid parallel simulated annealing algorithm with a new coding scheme is proposed. To analyze the performance of the proposed algorithm, 50 numerical examples with different budget types are examined and solved using the algorithm. The computational results of these comparisons show that the algorithm is an excellent approach in speed and solution quality. تفاصيل المقالة

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23 - Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory
Zaman Zamami Amlashi Mostafa Zandieh

This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly lin أکثر

This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this problem through some classical approaches such as total enumeration or exact mathematical procedures such as dynamic programming is computationally prohibitive. Therefore, we proposed the cloud theory-based simulated annealing algorithm (CSA) to address it. Previous researches indicates that evolutionary algorithms especially simulated annealing (SA) is an appropriate method to solve this problem; so we compared CSA with SA in this study to validate the proposed CSA algorithm. Experimentation shows that the CSA approach outperforms the SA approach in both CPU time and objective function especially in large size problems. تفاصيل المقالة

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24 - A Simulated Annealing Algorithm for Multi Objective Flexible Job Shop Scheduling with Overlapping in Operations
Mehrzad Abdi Khalife Babak Abbasi Amirhossein Kamali Dolat abadi

In 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 أکثر

In 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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25 - A New Approach in Job Shop Scheduling: Overlapping Operation
parviz Fattahi mohammad Saidi Mehrabad

In 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, أکثر

In 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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26 - Determination of Material Flows in a Multi-echelon Assembly SupplyChain
Mehrnoosh Taherkhani Mehdi Seifbarghy

This study aims to minimize the total cost of a four-echelon supply chain including suppliers, an assembler, distributers, and retailers. Thetotal cost consists of purchasing raw materials from the suppliers by the assembler, assembling the final product, materials tran أکثر

This study aims to minimize the total cost of a four-echelon supply chain including suppliers, an assembler, distributers, and retailers. Thetotal cost consists of purchasing raw materials from the suppliers by the assembler, assembling the final product, materials transportationfrom the suppliers to the assembler, product transportation from the assembler to the distributors, product transportation from thedistributors to the retailers, and product holding and stock-out in the distribution centers. To this end, having modeled the problemaddressed, a numerical example including ten suppliers, an assembler, three distributors and eight retailers in the chain is solved for fourperiods of time. Then the model is solved by a simulated annealing-based heuristic and LINGO. Finally, a set of 30 numerical problems ofsmall and large sizes are developed and solved. The results indicate that simulated annealing-based heuristic provides near optimalsolutions. تفاصيل المقالة

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27 - Hybrid Meta-heuristic Algorithm for Task Assignment Problem
Mohammad Jafar Tarokh Mehdi Yazdani Mani Sharifi Mohammad Navid Mokhtarian

Task assignment problem (TAP) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. TAP is a أکثر

Task assignment problem (TAP) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. TAP is a combinatorial optimization problem and NP-complete. This paper proposes a hybrid meta-heuristic algorithm for solving TAP in a heterogeneous distributed computing system. To compare our algorithm with previous ones, an extensive computational study on some benchmark problems was conducted. The results obtained from the computational study indicate that the proposed algorithm is a viable and effective approach for the TAP. تفاصيل المقالة

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28 - A Multi-level Capacitated Lot-sizing Problem with Safety Stock Deficit and Production Manners: A Revised Simulated Annealing
Esameil Mehdizadeh Mohammad Reza Mohammadizadeh

[1] Corresponding author e-mail: mehdi.foumani@monash.edu [1] Corresponding author e-mail: mehdi.foumani@monash.edu Lot-sizing problems (LSPs) belong to the class of production planning problems in which the availability quantities of the production pla أکثر

[1] Corresponding author e-mail: mehdi.foumani@monash.edu [1] Corresponding author e-mail: mehdi.foumani@monash.edu Lot-sizing problems (LSPs) belong to the class of production planning problems in which the availability quantities of the production plan are always considered as a decision variable. This paper aims at developing a new mathematical model for the multi-level capacitated LSP with setup times, safety stock deficit, shortage, and different production manners. Since the proposed linear mixed integer programming model is NP-hard, a new version of simulated annealing algorithm (SA) is developed to solve the model named revised SA algorithm (RSA). Since the performance of the meta-heuristics severely depends on their parameters, Taguchi approach is applied to tune the parameters of both SA and RSA. In order to justify the proposed mathematical model, we utilize an exact approach to compare the results. To demonstrate the efficiency of the proposed RSA, first, some test problems are generated; then, the results are statistically and graphically compared with the traditional SA algorithm. تفاصيل المقالة

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29 - Genetic Algorithm and Simulated Annealing for Redundancy Allocation Problem with Cold-standby Strategy
Aida Karimi Mani Sharifi Amirhossain Chambari

This paper presents a new mathematical model for a redundancyallocation problem (RAP) withcold-standby redundancy strategy and multiple component choices.The applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.M أکثر

This paper presents a new mathematical model for a redundancyallocation problem (RAP) withcold-standby redundancy strategy and multiple component choices.The applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.Manystudies have concentrated onone type of time-to-failure, butin thispaper, two components of time-to-failures which follow hypo-exponential and exponential distributionare investigated. The goal of the RAP is to select available components and redundancy level for each subsystem for maximizing system reliability under cost and weight constraints.Sincethe proposed model belongs to NP-hard class, we proposed two metaheuristic algorithms; namely, simulated annealing and genetic algorithm to solve it. In addition, a numerical example is presented to demonstrate the application of the proposed solution methodology. تفاصيل المقالة

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30 - A Tunned-parameter Hybrid Algorithm for Dynamic Facility Layout Problem with Budget Constraint using GA and SAA
Hani Pourvaziri Parham Azimi

A facility layout problem is concerned with determining the best position of departments, cells, or machines on the plant. An efficient layout contributes to the overall efficiency of operations. It’s been proved that, when system characteristics change, it can ca أکثر

A facility layout problem is concerned with determining the best position of departments, cells, or machines on the plant. An efficient layout contributes to the overall efficiency of operations. It’s been proved that, when system characteristics change, it can cause a significant increase in material handling cost. Consequently, the efficiency of the current layout decreases or is lost and it does necessitate rearrangement. On the other hand, the rearrangement of the workstations may burden a lot of expenses on the system. The problem that considers balance between material handling cost and the rearrangement cost is known as the Dynamic Facility Layout Problem (DFLP). The objective of a DFLP is to find the best layout for the company facilities in each period of planning horizon considering the rearrangement costs. Due to the complex structure of the problem, there are few researches in the literature which tried to find near optimum solutions for DFLP with budget constraint. In this paper, a new heuristic approach has been developed by combining Genetic Algorithm (GA) and Parallel Simulated Annealing Algorithm (PSAA) which is the main contribution of the current study. The results of applying the proposed algorithm were tested over a wide range of test problems taken from the literature. The results show efficiency of the hybrid algorithm GA- to solve the Dynamic Facility Layout Problem with Budget Constraint (DFLPBC). تفاصيل المقالة

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31 - Reliability Modelling of the Redundancy Allocation Problem in the Series-parallel Systems and Determining the System Optimal Parameters
Mani Sharifi Mohsen Yaghoubizadeh

Considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. In this study, we consider one of the current models of the reliability science and propose a non-linear programming أکثر

Considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. In this study, we consider one of the current models of the reliability science and propose a non-linear programming model for redundancy allocation in the series-parallel systems according to the redundancy strategy and considering the assumption that the failure rate depends on the number of the active elements. The purpose of this model is to maximize the reliability of the system. Internal connection costs, which are the most common costs in electronic systems, are used in this model in order to reach the real-world conditions. To get the results from this model, we used meta-heuristic algorithms such as genetic algorithm and simulation annealing after optimizing their operators’ rates by using response surface methodology. تفاصيل المقالة

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32 - A Heuristic Algorithm for Nonlinear Lexicography Goal Programming with an Efficient Initial Solution
Mahdi Bashiri Amir Hossein Parsa Manesh Hamid Hasanzadeh

In this paper, a heuristic algorithm is proposed in order to solve a nonlinear lexicography goal programming (NLGP) by using an efficient initial point. Some numerical experiments showed that the search quality by the proposed heuristic in a multiple objectives problem أکثر

In this paper, a heuristic algorithm is proposed in order to solve a nonlinear lexicography goal programming (NLGP) by using an efficient initial point. Some numerical experiments showed that the search quality by the proposed heuristic in a multiple objectives problem depends on the initial point features, so in the proposed approach the initial point is retrieved by Data Envelopment Analysis to be selected as an efficient solution. There are some weaknesses in classic NLGP algorithm that lead to trapping into the local optimum, so a simulated annealing concept is implemented during the searching stage to increase the diversity of search in the solution space. Some numerical examples with different sizes were generated and comparison of results confirms that the proposed solution heuristic is more efficient than the classic approach. Moreover the proposed approach was extended for cases with ordinal weights of inputs or outputs. The computational experiments for 5 numerical instances and the statistical analysis indicate that the proposed heuristic algorithm is a robust procedure to find better preferred solution comparing to the classic NLGP. تفاصيل المقالة

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33 - A multi-objective evolutionary approach for integrated production-distribution planning problem in a supply chain network
Keyvan Sarrafha Abolfazl Kazemi Alireza Alinezhad

Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer li أکثر

Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in supply chain and transfer time of products for retailers. From different terms of evolutionary computations, this paper proposes a Pareto-based meta-heuristic algorithm called multi-objective simulated annealing (MOSA) to solve the problem. To validate the results obtained, a popular algorithm namely non-dominated sorting genetic algorithm (NSGA-II) is utilized as well. Since the solution-quality of proposed meta-heuristic algorithm severely depends on their parameters, the Taguchi method is utilized to calibrate the parameters of the proposed algorithm. Finally, in order to prove the validity of the proposed model, a numerical example is solved and conclusions are discussed. تفاصيل المقالة

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34 - Provide a model for manpower scheduling using a hybrid meta-innovative algorithm in the Water and Sewerage Company
seyed ahmad shayan nia roghayeh mirataollahi olya

One 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 أکثر

One 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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35 - Using design of experiments approach and simulated annealing algorithm for modeling and Optimization of EDM process parameters
Masoud Azadi Moghaddam Farhad Kolahan Meysam Beytolamani

The main objectives of this research are, therefore, to assess the effects of process parameters and to determine their optimal levels machining of Inconel 718 super alloy. gap voltage, current, time of machining and duty factor are tuning parameters considered to be st أکثر

The main objectives of this research are, therefore, to assess the effects of process parameters and to determine their optimal levels machining of Inconel 718 super alloy. gap voltage, current, time of machining and duty factor are tuning parameters considered to be study as process input parameters. Furthermore, two important process output characteristic, have been evaluated in this research are material removal rate (MRR) and surface roughness (SR). Determination of a combination of process parameters to minimize SR and maximize MRR is the objective of this study. In order to gather required experimental data, design of experiments (DOE) approach, has been used. Then, statistical analyses and validation experiments have been carried out to select the best and the most fitted regression models. In the last section of this research, simulated annealing (SA) algorithm has been employed for optimization of the EDM process performance characteristics. A set of verification tests is also performed to confirm the accuracy of the proposed optimization procedure in determining the optimal levels of machining parameters. The results indicate that the proposed modeling technique and SA algorithm are quite efficient in modeling and optimization of EDM process parameters. تفاصيل المقالة

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36 - Simultaneously Modeling and Optimization of Heat Affected Zone and Tensile Strength in GTAW Process Using Simulated Annealing Algorithm
Meysam Beytolamani Masoud Azadi Moghaddam Farhad Kolahan

In the present study, a technique has been addressed in order to model and optimize gas tungsten arc welding (GTAW) process which is one of the mostly used welding processes based on the high quality fabrication acquired. The effects of GTAW process variables on the joi أکثر

In the present study, a technique has been addressed in order to model and optimize gas tungsten arc welding (GTAW) process which is one of the mostly used welding processes based on the high quality fabrication acquired. The effects of GTAW process variables on the joint quality of AISI304 stainless steel thin sheets (0.5 mm) have been investigated. The required data for modeling and optimization purposes has been gathered using Taguchi design of experiments (DOE) technique. Next, based on the acquired data, the modeling procedure has been performed using regression functions for two outputs; namely, heat affected zone (HAZ) width and ultimate tensile stress (UTS). Then, analysis of variance (ANOVA) has been performed in order to select the most fitted proposed models for single-objective and multi-criteria optimization of the process in such a way that UTS is maximized and HAZ width minimized using simulated annealing (SA) algorithm. Frequency, welding speed, base current and welding current are the most influential variables affecting the UTS at 22%, 21%, 20% and 17% respectively. Similarly, base current, welding current, frequency and welding speed affect the HAZ at 28%, 20%, 16%, and 15% respectively. Based on the results considering the lowest values for current results in the smallest amount of HAZ. By the same token in order to acquire the largest amount of UTSs the highest values of current must be considered. Setting welding and base current, frequency, speed, and debi at 42 and 5 apms, 46 Hz, 0.4495 m/min, and 5 lit/min respectively resulted the optimized HAZ and UTS simultaneously. The proper performance of the proposed optimization method has been proved through comparison between computational results and experimental data with less than 6% error. تفاصيل المقالة

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37 - Scheduling Problem of Virtual Cellular Manufacturing Systems (VCMS); Using Simulated Annealing and Genetic Algorithm based Heuristics
Saeed Taouji Hassanpour Reza Bashirzadeh Abolfazl Adressi Behnam Bahmankhah

In 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 أکثر

In 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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38 - بهینه‌سازی مسیریابی مقاوم به تاخیر با استفاده از الگوریتم اکتشافی شبیه‌سازی تبرید در شبکه‌های اقتضایی متحرک گسسته
سمیه پیرزادی محمدعلی پورمینا سید مصطفی صفوی همامی

با توجه به اینکه کاهش تاخیر در دریافت اطلاعات در شبکه‌های بی‌سیم گسسته در شرایط بحرانی حائز اهمیت است، جهت سرعت بخشیدن به انتقال پیام‌ها در شبکه‌های اقتضایی گسسته، پروتکل‌ مسیریابی ترکیبی با رویکرد ذخیره و حمل به جلو در معماری شبکه‌ مبتنی بر جعبه پرتاب با توجه به جنبه‌ه أکثر

با توجه به اینکه کاهش تاخیر در دریافت اطلاعات در شبکه‌های بی‌سیم گسسته در شرایط بحرانی حائز اهمیت است، جهت سرعت بخشیدن به انتقال پیام‌ها در شبکه‌های اقتضایی گسسته، پروتکل‌ مسیریابی ترکیبی با رویکرد ذخیره و حمل به جلو در معماری شبکه‌ مبتنی بر جعبه پرتاب با توجه به جنبه‌هایی مانند پیش‌بینی رله مناسب و مدیریت موثر بافر در این مقاله ارائه شده است. به‌منظور حفظ حداکثر نرخ انتقال موفق و کاهش زمان انتقال اطلاعات در معیارهای انتخاب گره رله علاوه بر در نظر گرفتن سوابق گره‌ها، تاثیر سه عامل مختلف تاخیر مبدا به مقصد، فضای بافر در دسترس گره‌ها و همچنین اطلاعاتی مانند متوسط سرعت و جهت حرکت گره‌ها در نظر گرفته شده است. همچنین با به‌کار بردن الگوریتم شبیه‌سازی تبرید از هوش مصنوعی در انجام مسیریابی بهینه استفاده می‌شود. جهت مطالعه عملکرد مدل ارائه شده معیارهای عملکرد مشترک مهمی مانند متوسط تاخیر، نسبت تحویل، تعداد پیام‌های از دست رفته و سربار شبکه مورد استفاده قرار گرفته است. نتایج نشان می‌دهد که روش مسیریابی پیشنهادی نسبت به سایر روش‌های مسیریابی علاوه بر حفظ حداکثر انتقال از تاخیر دریافت کمتری برخوردار است. تفاصيل المقالة

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39 - ارائه رویکردی جدید برای تشخیص حملات علیه صدا از طریق پروتکل اینترنت مبتنی بر خوشه‌بندی تجمیعی
فرید باوی فرد محمد خیراندیش محمد مصلح

با توجه به هزینه کمتر و انعطاف‌پذیری بیشتر، انتقال صدا از طریق پروتکل اینترنت (VoIP) به طور گسترده‌ای در ارتباطات راه دور استفاده می‌شود. تنوع پایانه‌های VoIP باعث آسیب‌پذیری آنها می‌شود. یک راه متداول برای ایمن‌سازی VoIP، شامل تشخیص نفوذ مبتنی بر یادگیری ماشین است. با أکثر

با توجه به هزینه کمتر و انعطاف‌پذیری بیشتر، انتقال صدا از طریق پروتکل اینترنت (VoIP) به طور گسترده‌ای در ارتباطات راه دور استفاده می‌شود. تنوع پایانه‌های VoIP باعث آسیب‌پذیری آنها می‌شود. یک راه متداول برای ایمن‌سازی VoIP، شامل تشخیص نفوذ مبتنی بر یادگیری ماشین است. با توجه به تنوع ترافیک و عدم وجود برچسب کلاس برای آموزش سیستم‌های تشخیص نفوذ (IDS) در بسیاری از مواقع، بر رویکردهای خوشه‌بندی (یادگیری بدون ناظر) متمرکز شده‌اند. اما سیستم‌های خوشه‌بندی منفرد نمی‌توانند تنوع مقادیر ویژگی‌ها را به خوبی پوشش دهند و برخی از نمونه‌های ترافیک ممکن است به عنوان نقاط پرت شناسایی شوند. مدل پیشنهادی، به‌عنوان یک رویکرد تجمیعی برای حل این مسائل، روی استفاده از الگوریتم خوشه‌بندی دومرحله‌ای متمرکز شده و سعی می‌کند با ایجاد بهبودی در آن، فرآیند تشخیص نفوذ مبتنی بر خوشه‌بندی را بهبود دهد. علاوه بر این، با توجه به اهمیت فرآیند انتخاب ویژگی، ترکیبی از الگوریتم شبیه‌سازی تبرید (SA) و شبکه عصبی پرسپترون چندلایه (MLP)، برای شناسایی ویژگی‌های برتر مورد استفاده در خوشه‌بندی بسته‌های VoIP، در قالب بسته‌های عادی یا حمله انکار سرویس (DoS)، حمله کاربر به ریشه (U2R)، حمله کاربر از راه دور (R2L) و حمله پویش‌گر مورد بهره‌‌برداری قرار گرفته است. بر اساس نتایج ارزیابی بر روی مجموعه داده "آزمایشگاه امنیت شبکه– کشف دانش در پایگاه‌های داده‌ای" ( NSL-KDD)، توسط نرم‌افزار متلب، انتخاب ویژگی پیشنهادی با کاهش ویژگی‌ها به 10 و 8، زمان آموزش و آزمایش را به‌ترتیب 77 درصد و 80 درصد کاهش می‌دهد. همچنین در مقایسه با تعدادی از مطالعات قبلی، IDS پیشنهادی بهبود متوسطی معادل 34/3 درصد، 17/14 درصد و 87/32 درصد را به‌ترتیب در دقت، نرخ تشخیص و معیار F نشان می‌دهد. تفاصيل المقالة

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40 - Stochastic Facility Layout Planning Problem: A Metaheuristic and Case Study
Nima Moradi

Facility layout is one of the most important Operations Management problems due to its direct impact on the financial performance of both private and public firms. Facility layout problem (FLP) with stochastic parameters, unequal area facilities, and grid system modelin أکثر

Facility layout is one of the most important Operations Management problems due to its direct impact on the financial performance of both private and public firms. Facility layout problem (FLP) with stochastic parameters, unequal area facilities, and grid system modeling is named GSUA-STFLP. This problem has not been worked in the literature so that to solve GSUA-STFLP is our main contribution. In this paper, we have first presented an integer nonlinear programming model which aims to minimize the cost of material handling. Then, a metaheuristic SA-based algorithm is proposed. Our proposed SA is able to generate feasible solutions by a local search operator to explore and exploit the solution space. Next, problems with different sizes besides the real case study have been solved. The computational results show the capability of the proposed SA to obtain the solutions with high quality in a short time. تفاصيل المقالة

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41 - meta-heuristic algorithms to solve the problem of terminal facilities on a real scale
مهدی فضلی فرزین مدرس خیابانی بهروز دانشیان

a b s t r a c tOur main goal in this article is to arrange terminal facilities, place different departments, stores and units in predefined areas in such a way as to minimize the cost of moving customers and transportation staff. Especially in large-scale terminals with أکثر

a b s t r a c tOur main goal in this article is to arrange terminal facilities, place different departments, stores and units in predefined areas in such a way as to minimize the cost of moving customers and transportation staff. Especially in large-scale terminals with several different transport segments, it is important for terminal performance to be close to interactive units. Today, meta-heuristic methods are often used to solve optimization problems such as facility design. in this study; The design of the various units, stores, and rooms of a large-scale real terminal was organized using three meta-heuristic algorithms: Migratory Bird Optimization (MBO), Taboo Search (TS), and Simulated Simulation (SA). The results were compared with the existing terminal design. As a result, MBO and SA metaheuristic algorithms have provided the best results, which improve the efficiency of the existing terminal design to an acceptable level. تفاصيل المقالة

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42 - Modeling and Optimization of Chemical Fertilizers Supply Chain using Hybrid Whale Optimization and Simulated Annealing
Motahareh Rabbani سید محمد حاجی مولانا Seyed Mojtaba Sajadi Mohammad Hossein Davoodi

Phosphorus is a basic constituent of chemical fertilizers and plays a pivotal role in crop yield enhancement in agriculture systems. Considering the growing demands for phosphorus and the limited resources of this vital substance, sustainable supply chain management (SC أکثر

Phosphorus is a basic constituent of chemical fertilizers and plays a pivotal role in crop yield enhancement in agriculture systems. Considering the growing demands for phosphorus and the limited resources of this vital substance, sustainable supply chain management (SCM) of chemical fertilizers is of great importance. In the present study, a mathematical model for sustainable chemical fertilizer SCM is presented. Taking into account the adverse environmental effects of the production and consumption of chemical fertilizers, the present study attempts to design a sustainable SCM concerning economic, environmental, and social factors. To solve the problem, a hybrid metaheuristic algorithm incorporating whale optimization and simulated annealing is used considering a multi-objective function. The simulation results obtained from a real case study of the chemical fertilizers supply chain network in Iran proved the effectiveness and applicability of the proposed model and solution method. Obtained results show the effectiveness of the proposed method compared with other algorithms with respect to economic, social, and environmental factors. تفاصيل المقالة

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43 - Cuckoo Optimization Algorithm in Cutting Conditions During Machining
Ahmad Esfandiari

Optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. In recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. The Cuc أکثر

Optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. In recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. The Cuckoo Optimization Algorithm (COA) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and their lifestyle. In this paper, COA, Simulated Annealing (SA), Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA) are first applied to five test functions and the performance of these algorithms is compared. These algorithms are then used to optimize the cutting conditions. The results showed that COA has more capabilities such as accuracy, faster convergence and better global optimum achievement than others. تفاصيل المقالة

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44 - A Comparative Study of Meta-heuristic Algorithms in Supply Chain Networks
Fariba Salahi Amir Daneshvar Mahdi Homayounfar Mohammad Shokouhifar

10.30495/jiei.2021.1919032.1076

Today, with the development of Information Technology (IT) and economic globalization, the suppliers’ selection has been emphasized in supply chain systems. Accordingly, artificial intelligence-based methods have attracted much attention. Hence, in this research, أکثر

Today, with the development of Information Technology (IT) and economic globalization, the suppliers’ selection has been emphasized in supply chain systems. Accordingly, artificial intelligence-based methods have attracted much attention. Hence, in this research, the selection of appropriate suppliers with respect to the multi-resource supply policy, and the implementation of lateral transshipment have been studied, and meta-heuristic algorithms have been employed to solve the problem. In the proposed method, the supply chain network is improved by minimizing the inventory shortages through utilizing lateral transshipment between different factories. In order toefficiently solve the problem, a hybrid meta-heuristic algorithm based on population-based genetic algorithm (GA) and single-solution simulated annealing (SA), named GASA, is propose, in order to simultaneously gain with the advantages of both algorithms, i.e., global search ability of GA and local search ability of SA. In order to compare the results of the proposed GASA, it is compared with GA and SA, to find the best solution. Given the parameters optimization and conducted analyses and comparisons of primary and hybrid algorithms performance, the hybrid GASA algorithm has been identified as the most efficient algorithm to solve the problem,compared to the other algorithms, emphasizing cost reduction and shortage volume. تفاصيل المقالة

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45 - A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems
Amir-Reza Abtahi Afsane Bijari

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the ad أکثر

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems. تفاصيل المقالة

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46 - A hybrid meta-heuristic algorithm for the vehicle routing problem with stochastic travel times considering the driver's satisfaction
Reza Tavakkoli-Moghaddam Mehdi Alinaghian Alireza Salamat-Bakhsh Narges Norouzi

A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function o أکثر

A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm. تفاصيل المقالة

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47 - Using and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators
Seyed Hosein Mousavi Ali Nazemi Ashkan Hafezalkotob

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The so أکثر

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous optimization of multiple parameters. The problem is formulated analytically using the Nash equilibrium concept for games composed of large numbers of players having discrete and large strategy spaces. The solution methodology is based on a characterization of Nash equilibrium in terms of minima of a function and relies on a metaheuristic optimization approach to find these minima. This paper presents some metaheuristic algorithms to simulate how generators bid in the spot electricity market viewpoint of their profit maximization according to the other generators’ strategies, such as genetic algorithm (GA), simulated annealing (SA) and hybrid simulated annealing genetic algorithm (HSAGA) and compares their results. As both GA and SA are generic search methods, HSAGA is also a generic search method. The model based on the actual data is implemented in a peak hour of Tehran’s wholesale spot market in 2012. The results of the simulations show that GA outperforms SA and HSAGA on computing time, number of function evaluation and computing stability, as well as the results of calculated Nash equilibriums by GA are less various and different from each other than the other algorithms. تفاصيل المقالة

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48 - An archived multi-objective simulated annealing for a dynamic cellular manufacturing system
Hossein Shirazi Reza Kia Nikbakhsh Javadian Reza Tavakkoli-Moghaddam

To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelate أکثر

To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features used in the design of CMSs and enhances the flexibility of an existing model in handling the fluctuations of part demands more economically by adding machine depot and PP decisions. Two conflicting objectives to be minimized are the total costs and the imbalance of workload among cells. As the considered objectives in this model are in conflict with each other, an archived multi-objective simulated annealing (AMOSA) algorithm is designed to find Pareto-optimal solutions. Matrix-based solution representation, a heuristic procedure generating an initial and feasible solution and efficient mutation operators are the advantages of the designed AMOSA. To demonstrate the efficiency of the proposed algorithm, the performance of AMOSA is compared with an exact algorithm (i.e., [-constraint method) solved by the GAMS software and a well-known evolutionary algorithm, namely NSGAII for some randomly generated problems based on some comparison metrics. The obtained results show that the designed AMOSA can obtain satisfactory solutions for the multi-objective model. تفاصيل المقالة

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49 - A hybrid CS-SA intelligent approach to solve uncertain dynamic facility layout problems considering dependency of demands
Ghorbanali Moslemipour

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density fu أکثر

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algorithm is proposed by combining the simulated annealing and clonal selection algorithms. The proposed model and the hybrid algorithm are verified and validated using design of experiment and benchmark methods. The results show that the hybrid algorithm has an outstanding performance from both solution quality and computational time points of view. Besides, the proposed model can be used in both of the stochastic and deterministic situations. تفاصيل المقالة

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50 - 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 Seyyedi

This 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 أکثر

This 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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51 - Solving an one-dimensional cutting stock problem by simulated annealing and tabu search
Meghdad HMA Jahromi Reza Tavakkoli-Moghaddam Ahmad Makui Abbas Shamsi

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In thi أکثر

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results are compared. The results show that the proposed SA gives good results in terms of objective function values rather than TS. تفاصيل المقالة

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52 - A new Simulated Annealing algorithm for the robust coloring problem
M.A Gutiérrez-Andrade P Lara-Velázquez S.G de-los-Cobos-Silva

The Robust Coloring Problem (RCP) is a generalization of the well-known Graph Coloring Problem where we seek for a solution that remains valid when extra edges are added. The RCP is used in scheduling of events with possible last-minute changes and study frequency assig أکثر

The Robust Coloring Problem (RCP) is a generalization of the well-known Graph Coloring Problem where we seek for a solution that remains valid when extra edges are added. The RCP is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. This problem has been proved as NP-hard and in instances larger than 30 vertices, meta-heuristics are required. In this paper a Simulated Annealing Algorithm is proposed, and his performance is compared against other tech-niques such as GRASP, Tabu Search and Scatter Search. In the classic instances of the problem our proposal method which gives the best solutions at this moment. تفاصيل المقالة

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53 - A multi-criteria vehicle routing problem with soft time windows by simulated annealing
R Tavakkoli-Moghaddam N Safaei M.A Shariat

This paper presents a multi-criteria vehicle routing problem with soft time windows (VRPSTW) to mini-mize fleet cost, routes cost, and violation of soft time windows penalty. In this case, the fleet is heterogene-ous. The VRPSTW consists of a number of constraints in wh أکثر

This paper presents a multi-criteria vehicle routing problem with soft time windows (VRPSTW) to mini-mize fleet cost, routes cost, and violation of soft time windows penalty. In this case, the fleet is heterogene-ous. The VRPSTW consists of a number of constraints in which vehicles are allowed to serve customers out of the desirable time window by a penalty. It is assumed that this relaxation affects customer satisfaction and penalty is equal to a degree of customer dissatisfaction. The VRP, which is an extension of traveling sales-man problem (TSP), belongs to a class of NP-hard problems. Thus, it is necessary to use meta-heuristics for solving VRP in large-scale problems. This paper uses a simulated annealing (SA) approach with 1-Opt and 2-Opt operators for solving the proposed mathematical model. The proposed model is then solved by the Lingo software and the associated solutions are compared with the computational results obtained by the SA ap-proach for a number of instance problems. The obtained results are promising and indicating the efficiency of the proposed SA approach. تفاصيل المقالة

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54 - Two-machine robotic cell considering different loading and unloading times
A.M Kimiagari H Mosadegh

In this paper, the researchers have investigated a Concatenated Robot Move (CRM) sequence problem and Minimal Part Set (MPS) schedule problem with different setup times for two-machine robotic cell. They have focused on simultaneous solving of CRM sequence and MPS sched أکثر

In this paper, the researchers have investigated a Concatenated Robot Move (CRM) sequence problem and Minimal Part Set (MPS) schedule problem with different setup times for two-machine robotic cell. They have focused on simultaneous solving of CRM sequence and MPS schedule problems with different loading and unloading times. They have applied a Simulated Annealing (SA) algorithm to provide a good solution rapidly. A domination rule has been developed and used in SA algorithm that strongly reduces the search space and increases speed and solution's quality of the algorithm. Numerical experiments indicate the results of the proposed SA from two points of view: quality of solution and consumed time. تفاصيل المقالة

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55 - An algorithm for multi-objective job shop scheduling problem
Parviz Fattahi Mohammad Saidi Mehrabad Mir B. Aryanezhad

Scheduling 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 أکثر

Scheduling 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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56 - Multi-start simulated annealing for dynamic plant layout problem
B Ashtiani M.B Aryanezhad B Farhang Moghaddam

In today’s dynamic market, organizations must be adaptive to market fluctuations. In addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. Therefore, this paper considers the problem of arranging and rea أکثر

In today’s dynamic market, organizations must be adaptive to market fluctuations. In addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. Therefore, this paper considers the problem of arranging and rearranging, when there are changes in product mix and demand, manufacturing facilities such that the sum of material handling and rearrangement costs is minimized. This problem is called the dynamic plant layout problem (DPLP). In this paper, the authors develop a multi-start simulated annealing for DPLP. To compare the performance of meta-heuristics, data sets taken from literature are used in the comparison. تفاصيل المقالة

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57 - The trim loss concentration in one-dimensional cutting stock problem (1D-CSP) by defining a virtual cost
H Javanshir M Shadalooee

Nowadays, One-Dimensional Cutting Stock Problem (1D-CSP) is used in many industrial processes and re-cently has been considered as one of the most important research topic. In this paper, a metaheuristic algo-rithm based on the Simulated Annealing (SA) method is represe أکثر

Nowadays, One-Dimensional Cutting Stock Problem (1D-CSP) is used in many industrial processes and re-cently has been considered as one of the most important research topic. In this paper, a metaheuristic algo-rithm based on the Simulated Annealing (SA) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. In this method, the 1D-CSP is taken into account as Item-oriented and the authors have tried to minimize the trim loss concentration by using the simulated an-nealing algorithm and also defining a virtual cost for the trim loss of each stock. The solved sample problems show the ability of this algorithm to solve the 1D-CSP in many cases. تفاصيل المقالة

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58 - EPQ model with depreciation cost and process quality cost as continuous functions of time
B Afshar Nadjafi B Abbasi

Extensive research has been devoted to economic production quantity (EPQ) problem. However, little atten-tion has been paid to problems where depreciation cost and process quality cost must be considered, simulta-neously. In this paper, we consider the economic producti أکثر

Extensive research has been devoted to economic production quantity (EPQ) problem. However, little atten-tion has been paid to problems where depreciation cost and process quality cost must be considered, simulta-neously. In this paper, we consider the economic production quantity model of minimizing the annual total cost subject to depreciation cost and process quality cost, where depreciation cost and process quality cost are assumed to be continuous functions of holding time and of production run length, respectively. Local search meta-heuristics: iterated local search (ILS) and simulated annealing (SA) are proposed to solve proposed model. Finally, the meta-heuristics are computationally compared by using some numerical examples and re-sults are analyzed. تفاصيل المقالة

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59 - A New Optimal Correlation for Behavior factor of EBFs under Near-fault Earthquakes using Artificial Intelligence Models
Seyed Abdonnabi Razavi Navid Siahpolo

10.1007/ijase.2022.698628

Behavior factor of the structures is a coefficient that includes the inelastic performance of the structure and indicates the hidden resistance of the structure in the inelastic stage. In most seismic codes, this coefficient is merely dependent on the type of lateral re أکثر

Behavior factor of the structures is a coefficient that includes the inelastic performance of the structure and indicates the hidden resistance of the structure in the inelastic stage. In most seismic codes, this coefficient is merely dependent on the type of lateral resistance system and is introduced with a fixed number. However, there is a relationship between the behavior factor, ductility (performance level), structural geometric properties, and type of earthquake (near and far). In this paper, a new optimal correlation is attempted to predict the behavior factor (q) of EBF steel frames, under near-fault earthquakes, using Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms. For this purpose, a databank consists of 12960 data created. To establishing different geometrical properties of models, 3-,6-, 9-, 12-, 15, 20- stories steel EBF frames considered with 3 different types of link beam, 3 different types of column stiffness and 3 different types of brace slenderness. Using nonlinear time history under 20 near-fault earthquake, all models analyzed to reach 4 different performance level. data were used as training data of the Artificial Intelligence Models. Results shows the high accuracy of proposed correlation, established by PSO algorithm. The results of the correlation between the studied algorithms show more accuracy in the relations produced than the previous algorithms and confirm the significance of the governing relations. تفاصيل المقالة

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60 - شبکه‌های اسپینی بستری برای پردازش توزیع شده: مطالعه موردی حل مسئله انتخاب بهینه‌سبدسهام
مجید وفایی جهان محمدرضا اکبرزاده&lrm;توتونچی

امروزه خواص فیزیکی اجسام، دستاویزی برای حل مسائل بهینه‌سازی است تا پاسخ بهینه مسائل با تعداد حالات زیاد سریع‌تر و دقیق‌تر یافته شود. به‌عنوان نمونه می‌توان به الگوریتم‌‌های بهینه‌سازی مبتنی بر اسپین‌گلاس (شبکه‌های اسپینی)‌ اشاره کرد که به‌دلیل داشتن قابلیت جستجوی محلی و أکثر

امروزه خواص فیزیکی اجسام، دستاویزی برای حل مسائل بهینه‌سازی است تا پاسخ بهینه مسائل با تعداد حالات زیاد سریع‌تر و دقیق‌تر یافته شود. به‌عنوان نمونه می‌توان به الگوریتم‌‌های بهینه‌سازی مبتنی بر اسپین‌گلاس (شبکه‌های اسپینی)‌ اشاره کرد که به‌دلیل داشتن قابلیت جستجوی محلی و پردازش توزیع شده مورد توجه قرار دارند. از آنجایی که شبکه‌های اسپینی، بیشتر مبتنی بر الگوریتم‌های تصادفی - مونت‌کارلو همچون تبرید تدریجی (SA) برای یافتن حالت بهینه استفاده می‌کنند، از سرعت همگرایی پائینی برخورداند. بنابراین برای افزایش سرعت، از الگوریتم‌های بهینه‌سازی اکتشافی، تکاملی و غیره استفاده می‌شود. در این مقاله با در نظر گرفتن قابلیت شبکه‌اسپینی در حل مسائل بهینه‌سازی،کوشش شده است یکی از مسائل غیرچندجمله‌ای (NP) با عنوان مسئله انتخاب بهینه سبدسهام با استفاده از تبرید تدریجی حل شود؛ سپس با توجه به خواص توزیع‌شده‌گی اینگونه از شبکه‌ها، الگوریتم جدید مبتنی بر اتوماتای‌یادگیر(LA) بعنوان پردازش متمرکزو همچنین بهینه‌سازی‌اکسترمال (EO) بعنوان پردازش توزیع شده، ارائه گردیده است. نتایج آزمایش‌ها نشان می‌دهند که هرچند دو الگوریتم ارائه شده از حیث عملکرد، متفاوتند؛ ‌‌‌‌ولی هردو در محدوده پاسخ، تقریبا توزیع احتمال یکسانی برای انتخاب اسپین‌های برتر فراهم می‌کنند. به عبارت دیگر این دو روش از مرحله‌‌ای به بعد، شبیه هم عمل کرده و نتایج یکسانی تولید می‌کنند و کارایی شبکه‌های اسپینی از حیث سرعت همگرایی با حفظ دقت را به مقدار زیادی افزایش می‌دهند. همچنین دستاوردها نشان می‌دهد که انتخاب روش مبتنی بر LA یا EO برای شبکه‌های با تعداد اسپین‌کم تفاوتی ندارد؛ اما برای شبکه‌های بزرگ، EO که توانایی پردازش توزیع شده منحصر بفردی دارد، بسیار بهتر از روش‌های مبتنی بر یادگیری پاسخ می‌دهد که نتایج آزمایش‌های حاصل بر 5 بورس معتبر دنیا این موضوع را تائید می‌کند. تفاصيل المقالة

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61 - AN ELECTROMAGNETISM-LIKE ALGORITHM FOR FIXED CHARGE SOLID TRANSPORTATION PROBLEM
Masoud Sanei Ali Mahmoodirad Saber Molla-Alizadeh-Zavardehi

Fixed charge solid transportation problem (FCSTP) is one of the main and most important problems in transportation and network research areas. To tackle such an NP-hard problem, An Electromagnetism-like algorithm (EM) is employed. To the best of our knowledge, EM has be أکثر

Fixed charge solid transportation problem (FCSTP) is one of the main and most important problems in transportation and network research areas. To tackle such an NP-hard problem, An Electromagnetism-like algorithm (EM) is employed. To the best of our knowledge, EM has been considered for any kind of transportation problems. Due to the significant role of parameters on the algorithm’s performance, a calibration in EM is carried out with the aid of a set of experimental design. The efficiency of employed parameters is measured by the experimental design method. To evaluate the performance of the proposed EM, a computational study has been conducted and the associated results obtained by the EM are compared with simulated annealing algorithm (SA). تفاصيل المقالة

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