NSGA-II

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1 - An Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Hanieh Ghorashi Meghdad Mirabi

Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduli أکثر

Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distributed system in order to optimize resource utilization and response time. In this paper, an optimization-based method for task scheduling is presented in order to improve the efficiency of cloud computing. In the proposed approach, three criteria for scheduling, including the task execution time, the task transfer time, and the cost of task execution have been considered. Our method not only reduces the execution time of the overall tasks but also minimizes the maximum time required for task execution. We employ the Multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) for solving the scheduling problem. To evaluate the efficiency of the proposed method, a real cloud environment is simulated, and a similar method based on Multi-Objective Particle Swarm Optimization is applied. Experimental results show the superiority of our approach over the baseline technique. تفاصيل المقالة

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2 - مدلسازی و مقایسه بهینه‌یابی‌های تکاملی فازی و غیرفازی چند‌هدفه سبد سرمایه‌گذاری در بورس اوراق بهادار تهران
محمد فلاح هادی خواجه زاده دزفولی حامد نوذری

انتخاب و تشکیل سبد سهام بهینه، یکی از مهمترین‌ مسائل در حوزه تحقیقات مالی است که موجب می‌شود ترکیب بهینه‌ای از دارایی‌ها را انتخاب شود تا با توجه به محدودیت‌ها، بیشینه مطلوبیت برای سرمایه‌گذار ایجاد شود. با توجه به آن‌که بازده اوراق بهادار در دنیای واقعی معمولاً مبهم و أکثر

انتخاب و تشکیل سبد سهام بهینه، یکی از مهمترین‌ مسائل در حوزه تحقیقات مالی است که موجب می‌شود ترکیب بهینه‌ای از دارایی‌ها را انتخاب شود تا با توجه به محدودیت‌ها، بیشینه مطلوبیت برای سرمایه‌گذار ایجاد شود. با توجه به آن‌که بازده اوراق بهادار در دنیای واقعی معمولاً مبهم و نادقیق است، یکی از مهمترین چالش‌های سرمایه‌گذاری، عدم‌اطمینان نسبت به آینده و پیامدهای آن‌ها می‌باشد. بر این اساس، در این مقاله، با استفاده از گشتاورهای مراتب بالا و تئوری فرامدرن پرتفوی، و با استفاده از منطق فازی و بهینه‌یابی تکاملی چندهدفه، مسأله انتخاب و بهینه‌یابی پرتفوهای اوراق بهادار با اهداف مختلف مدلسازی، حل و مقایسه گردیده است. مدل‌های طراحی شده هم طبیعت مسأله انتخاب پرتفو را در نظر گرفته و هم ملاحظات مدنظر سهامدار را در انتخاب پرتفو دخیل نموده است. کیفیت عدم اطمینان بازده آتی پرتفوی داده شده با استفاده از اعداد LR فازی تخمین زده شده در حالیکه گشتاورهای بازدهی آن با استفاده از تئوری امکانی سنجیده شده است. مهمترین هدف این مقاله حل مسأله و مقایسه مدل‌های انتخاب پرتفوی به صورت بهینه‌سازی همزمان دو، سه و چهار هدفه است. برای این هدف، از الگوریتم ژنتیک با مرتب‌سازی نامغلوب (NSGA-II)استفاده شده و عملگرهای جهش و تقاطع به طور اختصاصی برای تولید راه‌حل‌های ممکن محدودیت کاردینالیتی مسأله طراحی شده است. در نهایت عملکرد مدل‌ها در صورت استفاده از منطق فازی و عدم استفاده از آن مقایسه شده است و مشخص گردیده است که استفاده از منطق فازی و تئوری امکانی، باعث تشکیل پرتفوهای با عملکرد بالاتر و مطلوببیت بیشتر می‌گردد. تفاصيل المقالة

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3 - ارائه یک مدل دوهدف تخصیص عضو مازاد برای بهینه سازی هزینه و قابلیت اطمینان یک سیستم سری –موازی و حل آن با استفاده
محمدرضا شهریاری

با توجه به افزایش عمومی توجه به مقوله کیفیت، توجه به بحث بهینه سازی قابلیت اطمینان در مرحله طراحی از اولویت بالایی برخوردار شده است. این تحقیق بر روی یکی از مدلهای موجود در علم قابلیت اطمینان به نام مسئله تخصیص افزونگی متمرکز شده و یک مدل دو هدفه برای این مسئله با أکثر

با توجه به افزایش عمومی توجه به مقوله کیفیت، توجه به بحث بهینه سازی قابلیت اطمینان در مرحله طراحی از اولویت بالایی برخوردار شده است. این تحقیق بر روی یکی از مدلهای موجود در علم قابلیت اطمینان به نام مسئله تخصیص افزونگی متمرکز شده و یک مدل دو هدفه برای این مسئله با سیستم سری-موازی ارائه شده است که در آن نرخ خرابی اجزاء وابسته به تعداد اجزاء فعال میباشد. اهداف این مسئله عباتند از افزایش قابلیت اطمینان سیستم و کاهش هزینه کل تخصی اجزاء. همچنین جهت نزدیک تر شدن این مسئله به جهان واقعی هزینه اتصال داخلی اجزاء نیز به مسئله اضافه شده است که در حوزه الکترونیک یک بحث بسیار متداول میباشد. با توجه به آنکه مسئله تخصیص افزونگی متعلق به دسته مسائل NP. Hard میباشد برای حل مسئله ارائه شده از الکوریتم NSGA-II استفاده شده و برای تنظیم پارامترهای مدل نیز از روش رویه پاسخ استفاده شده است.   تفاصيل المقالة

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4 - Fault Tolerance and Interference Aware Topology Control in Wireless Sensor Networks using NSGA-II
Nahid Sarbandi Farahani Asad Vakili

Research on topology control protocols in wireless sensor networks has often been designed with the goal of creating a dynamic topology and extensibility. The present study focuses on finding high quality paths, instead of minimizing the number of hops that can cause re أکثر

Research on topology control protocols in wireless sensor networks has often been designed with the goal of creating a dynamic topology and extensibility. The present study focuses on finding high quality paths, instead of minimizing the number of hops that can cause reduction of the received signal strength and maximizing the rate of loss. The purpose of this research is to create a topology control that focuses on reducing the fault and minimizing interference simultaneously. For this purpose, the fault rate and the degree of interference minimizing functions are modeled by using a two-objective genetic algorithm. Since the genetic algorithm is a revelation algorithm, the proposed method is compared in terms of convergence with similar algorithms. The obtained graphs show that the proposed algorithm has a good degree of convergence compared to similar models. The "runtime", "memory consumption" and "energy required to transmit the statement" are the variables used to compare with similar algorithms. By observing the obtained graphs, the proposed algorithm compared to similar methods, reduces the time needed for topology control and also it lowers the energy consumption, but is not able to reduce memory consumption for more packages. The main reason for conducting the test is the comparison of the quality of the routes created, which were executed in 20 different requests with the number of routes 5, 10 and 20. The quality of the routes produced by the proposed method has a 1% improvement over the SMG method and a 3% compared to the PSO method according to the route quality criteria. تفاصيل المقالة

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5 - Development of closed-loop supply chain mathematical model (cost-benefit-environmental effects) under uncertainty conditions by approach of genetic algorithm
Sadegh Feizollahi Heresh Soltanpanah Ayub Rahimzadeh

10.22034/amfa.2019.1864186.1198

In the current world, the debate on the reinstatement and reuse of consumer prod-ucts has become particularly important. Since the supply chain of the closed loop is not only a forward flow but also a reverse one; therefore, companies creating integ-rity between direct أکثر

In the current world, the debate on the reinstatement and reuse of consumer prod-ucts has become particularly important. Since the supply chain of the closed loop is not only a forward flow but also a reverse one; therefore, companies creating integ-rity between direct and reverse supply chain are successful. The purpose of this study is to develop a new mathematical model for closed loop supply chain net-work. In the real world the demand and the maximum capacity offered by the sup-plier are uncertain which in this model; the fuzzy theory discussion was used to cover the uncertainty of the mentioned variables. The objective functions of the model include minimizing costs, increasing revenues of recycling products, increas-ing cost saving from recycling and environmental impacts. According to the NP-hard, an efficient algorithm was suggested based on the genetic Meta heuristic algo-rithm to solve it. Twelve numerical problems were defined and solved using the NSGA-II algorithm to validate the model تفاصيل المقالة

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6 - حل مسئله زمانبندی پروژه با محدودیت منابع چندهدفه در حالت چند مد با الگوریتم زنبورهای عسل چندهدفه
Amir Sadeghi Sina Namazi Zahra Ghorajehlo Behnam Rezvanpour

مساله زمان‌بندی پروژه با منابع محدود، در واقع کلی ترین مساله زمان‌بندی است. مسائل زمان‌بندی کارگاهی ، جریان کارگاهی ، زمان‌بندی و سایر مسائل زمان‌بندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. در این مقاله مسئله زمانبندی پروژه با محدودیت منابع در حالت چند مد و رو أکثر

مساله زمان‌بندی پروژه با منابع محدود، در واقع کلی ترین مساله زمان‌بندی است. مسائل زمان‌بندی کارگاهی ، جریان کارگاهی ، زمان‌بندی و سایر مسائل زمان‌بندی همگی زیر مجموعه ای از این مسئله به حساب می آیند. در این مقاله مسئله زمانبندی پروژه با محدودیت منابع در حالت چند مد و روابط پیش نیازی جزئی در حالت مدل چندهدفه پیشنهاد شده است. در جهت کاربردی تر کردن بیش از پیش این مسئله مشهور اهداف مهم و کاربردی از قبیل کمینه کردن زمان اتمام پروژه و بیشینه کردن کیفیت انجام فعالیت های پروژه و کمینه کردن هزینه کل پروژه در نظر گرفته شده است. پس از اعتبار دهی مدل با استفاده از الگوریتم زنبورهای عسل به حل این مدل چند هدفه پیشنهادی، پرداخته شده است و نتایج عملکرد، با الگوریتم NSGA-II مقایسه شده است. نتایج نشان دهنده این است که الگوریتم پیشنهادی عملکرد مناسبی در حل این گونه مسائل داشته است. تفاصيل المقالة

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7 - ارائه مدل ترکیبی چند هدفه دوسطحی برای مساله مدیریت موجودی یک فروشنده و چند خرده فروش با استفاده از دو الگوریتم فرا ابتکاری چندهدفه مبتنی بر پارتو
مصطفی حسین نژادی علیرضا ایرج پور

در این پژوهش یک مدل ریاضیVMI ارائه خواهد شد. یک هدف مبنی بر کاهش هزینه های موجودی کالاها در زنجیره تامین دوسطحی است و هدف‌های دیگر به دنبال توانمندسازی سیستم و کمک به تصمیم گیری در شرایط تقاضای احتمالی و زمان های تحویل احتمالی و همچنین افزایش سطح خدمت و کیفیت و نیز کاهش أکثر

در این پژوهش یک مدل ریاضیVMI ارائه خواهد شد. یک هدف مبنی بر کاهش هزینه های موجودی کالاها در زنجیره تامین دوسطحی است و هدف‌های دیگر به دنبال توانمندسازی سیستم و کمک به تصمیم گیری در شرایط تقاضای احتمالی و زمان های تحویل احتمالی و همچنین افزایش سطح خدمت و کیفیت و نیز کاهش هزینه های افزایش سطح خدمت خواهد بود. همچنین، برای کارایی بیشتر در مسائل دنیای واقعی محدودیت هایی مانند وجود کمبود و سطح خدمت، فضای انبار، بودجه، ظرفیت انتقال، و نیز تخفیف کلی خواهیم داشت. محموله ها غیرهمسان فرض شده و کمبودها به دو صورت پس افت و فروش از دست رفته در نظر گرفته می شوند. ازآنجا که مدل به دست آمده از نوع برنامه ریزی عدد صحیح غیرخطی و اینکه مساله Np-Hard است، لذا باید از روش‌های حل فرا ابتکاری استفاده نمود. در آخر هدف این پژوهش ارایه مدل ریاضی مدیریت موجودی توسط فروشنده در زنجیره تامین در حالت هایی همچون یک خرده فروش - یک فروشنده، یک فروشنده – چند خرده فروش همراه با ارائه راه حل در شرایط عدم قطعیت و غیر همسان بودن محموله‌ها با مجاز بودن کمبود پس افت و فروش از دست رفته با تخفیف کلی است. تفاصيل المقالة

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8 - A Bi-Objective Airport Gate Scheduling with Controllable Processing Times Using Harmony Search and NSGA-II Algorithms
Morteza khakzar Bafruei Sananz khatibi Morteza Rahmani

10.22094/joie.2018.234

Optimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this أکثر

Optimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this research line shows thatin almost all studies airport gate processing time has been considered as a fix parameter. In this research, however, we investigate a more realistic situation in which airport gate processing time is a controllable. It is also assumed that the possible compression/expansion processing time of a flight can be continuously controlled, i.e. it can be any number in a given interval.Doing sohas some positive effectswhich lead to increasing the total performance at airports’ terminals. Depending on the situation, different objectives become important.. Therefore, a model which simultaneously (1) minimize the total cost of tardiness, earliness, delay andthe compression as well as the expansion costs of job processing time, and (2) minimize passengers overcrowding on gate is presented. In this study, we first propose a mixed-integer programming model for the formulated problem. Due to complexity of problem, two multi-objective meta-heuristic algorithms, i.e. multi-objective harmony search algorithm (MOHSA) and non-dominated sorting genetic algorithm II (NSGA-II) are applied in order to generate Pareto solutions. For calibrating the parameter of the algorithms, Taguchi method is used and three optimal levels of the algorithm’s performance are selected. The algorithms are tested with real-life data from Mehrabad International Airport for nine medium size test problems. The experimental results show that NSGA-II has better convergence near the true Pareto-optimal front as compared to MOHSA; however, MOHSA finds a better spread in the entire Pareto-optimal region.Finally, it is possible to apply some practical constraints into the model and also test them with even large real-life problems instances. تفاصيل المقالة

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9 - Monitoring process variability: a hybrid Taguchi loss and multiobjective genetic algorithm approach
Heng-Soon Gan Abdul Sattar Safaei

10.22094/joie.2016.245

The common consideration on economic model is that there is knowledge about the risk of occurrence of an assignable cause and the various cost parameters that does not always adequately describe what happens in practice. Hence, there is a need for more realistic assumpt أکثر

The common consideration on economic model is that there is knowledge about the risk of occurrence of an assignable cause and the various cost parameters that does not always adequately describe what happens in practice. Hence, there is a need for more realistic assumptions to be incorporated. In order to reduce cost penalties for not knowing the true values of some parameters, this paper aims to develop a bi-objective model of the economic-statistical design of the S control chart to minimize the mean hourly loss cost while minimizing out-of-control average run length and maintaining reasonable in-control average run length considering Taguchi loss function. The purpose of Taguchi loss function is to reflect the economic loss associated with variation in, and deviations from, the process target or the target value of a product characteristic. In contrast to the existing modeling approaches, the proposed model and given Pareto-optimal solution sets enables the chart designer to obtain solutions that is effective even for control chart design problems in uncertain environments. A comparison study with a traditional economic design model reveals that the proposed chart presents a better approach for quality system costs and the power of control chart in detecting the assignable cause. تفاصيل المقالة

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10 - Multi-Objective Optimization for Multi-Product Multi-Period Four Echelon Supply Chain Problems Under Uncertainty
Md Mashum Billal Md. Mosharraf Hossain

10.22094/joie.2018.555578.1529

The multi-objective optimization for a multi-product multi-period four-echelon supply chain network consisting of manufacturing plants, distribution centers (DCs) and retailers each with uncertain services and uncertain customer nodes are aimed in this paper. The two ob أکثر

The multi-objective optimization for a multi-product multi-period four-echelon supply chain network consisting of manufacturing plants, distribution centers (DCs) and retailers each with uncertain services and uncertain customer nodes are aimed in this paper. The two objectives are minimization of the total supply chain cost and maximization of the average number of products dispatched to customers. The decision variables are the number and the locations of reliable DCs and retailers, the optimum number of items produced by plants, the optimum quantity of transported products, the optimum inventory of products at DCs, retailers and plants, and the optimum shortage quantity of the customer nodes. The problem is first formulated into the framework of a constrained multi-objective mixed integer linear programming model. After that, the problem is solved by using meta-heuristic algorithms that are Multi-objective Genetic Algorithm (MOGA), Fast Non-dominated Sorting Genetic Algorithms (NSGA-II) and Epsilon Constraint Methods via the MATLAB software to select the best in terms of the total supply chain cost and the total expected number of products dispatched to customers simultaneously. At the end, the performance of the proposed multi-objective optimization model of multi-product multi-period four-echelon supply chain network design is validated through three realizations and an innumerable of various analyses in a real world case study of Bangladesh. The obtained outcomes and their analyses recognize the efficiency and applicability of the proposed model under uncertainty. تفاصيل المقالة

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11 - A Two-dimensional Warranty Model with Consideration of Customer and Manufacturer Objectives Solved with Non-dominated Sorting Genetic Algorithm
Amin Asadi Mohammad Saidi-Mehrabad Faranak Fathi Aghdam

10.22094/joie.2018.538225

Warranty is a powerful implement for marketing strategy that is used by manufacturersand creates satisfaction for consumers by ensuring to compensate for incorrect operation of the product. Warranty serviceresults ina cost named warranty cost for a manufacturer.This cos أکثر

Warranty is a powerful implement for marketing strategy that is used by manufacturersand creates satisfaction for consumers by ensuring to compensate for incorrect operation of the product. Warranty serviceresults ina cost named warranty cost for a manufacturer.This cost is a function of warranty policy, regions, and product failures pattern. Since this service coversthe cost of uncertain failure of the product, it makes some utility for customers. In this paper, we developed a novel customer utility function that is used as a customer objective to be maximized. In addition to the manufacturer objective, minimizing the warranty costisconsidered simultaneously. There are four restrictions on warranty parameters such as time, usage, unit product price and the R&D expenditure to be considered. Finally, we will propose a novel bi-objective model that maximizesthe utility function for customers and minimizesthe warranty cost for the manufacturer. This model will be solved with an evolutionary algorithmcalled Non-Dominated Sorting Genetic Algorithm (NSGA-II) and non-dominated Pareto solutionswill be gained from this method.To give a numerical instance, for a certain usage rate’s range of costumers, different warranties are provided and compared. It is believed that the computational results can help manufacturers to determine optimal solutions for the objective functions and consequentlywarranty parameters. تفاصيل المقالة

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12 - A Non-dominated Sorting Ant Colony Optimization Algorithm Approach to the Bi-objective Multi-vehicle Allocation of Customers to Distribution Centers
Jafar Bagherinejad Mina Dehghani

10.22094/joie.2016.230

Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to di أکثر

Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimization tool for solving this problem. The proposed methodology is based on a new variant of ant colony optimization (ACO) specialized in multi-objective optimization problem. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this purpose. For ensuring the robustness of the proposed method and giving a practical sense of this study, the computational results are compared with those obtained by NSGA-II algorithm. Results show that both NSACO and NSGA-II algorithms can yield an acceptable number of non-dominated solutions. In addition, the results show while the distribution of solutions in the trade-off surface of both NSACO and NSGA-II algorithms do not differ significantly, the computational CPU time of NSACO is considerably lower than that of NSGA-II. Moreover, it can be seen that the fast NSACO algorithm is more efficient than NSGA-II in the viewpoint of the optimality and convergence. تفاصيل المقالة

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13 - Developing a New Bi-Objective Functions Model for a Hierarchical Location-Allocation Problem Using the Queuing Theory and Mathematical Programming
Parham Azimi Abulfazl Asadollahi

10.22094/joie.2018.350.0

In this research, a hierarchical location-allocation problem is modeled in a queue framework. The queue model is considered as M/M/1/k, in which system capacity is finite, equals to k. This is the main contribution of the current research. Customer's enters to the syste أکثر

In this research, a hierarchical location-allocation problem is modeled in a queue framework. The queue model is considered as M/M/1/k, in which system capacity is finite, equals to k. This is the main contribution of the current research. Customer's enters to the system in order to find the service according to a Poisson. In this problem, the hierarchical location-allocation model is considered in two levels. Also, the model has two objective functions: maximizing the total number of demand coverage and minimizing the waiting time of customers in queues to receive services. After modeling and verifying the validity of the presented model, it is solved using NSGA II and MOPSO meta-heuristics. تفاصيل المقالة

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14 - A New Bi-objective Mathematical Model to Optimize Reliability and Cost of Aggregate Production Planning System in a Paper and Wood Company
Mohammad Ramyar Esmaeil Mehdizadeh Seyyed Mohammad Hadji Molana

10.22094/joie.2018.558585.1539

In this research, a bi-objective model is developed to deal with a supply chain including multiple suppliers, multiple manufacturers, and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem. This bi-object أکثر

In this research, a bi-objective model is developed to deal with a supply chain including multiple suppliers, multiple manufacturers, and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem. This bi-objective model aims to minimize the total cost of supply chain including inventory costs, manufacturing costs, work force costs, hiring, and firing costs, and maximize the minimum of suppliers' and producers' reliability by the considering probabilistic lead times, to improve the performance of the system and achieve a more reliable production plan. To solve the model in small sizes, a ε-constraint method is used. A numerical example utilizing the real data from a paper and wood industry is designed and the model performance is assessed. With regard to the fact that the proposed bi-objective model is NP-Hard, for large-scale problems one multi-objective harmony search algorithm is used and its results are compared with the NSGA-II algorithm. The results demonstrate the capability and efficiency of the proposed algorithm in finding Pareto solutions. تفاصيل المقالة

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15 - Multi-objective Optimization of Turning of Titanium Alloy Under Minimum Quantity Lubrication
Satish Chinchanikar Jitendra Katiyar Omkar Manav

10.22094/joie.2021.1937743.1886

In the present study, the machining performance of titanium grade-1 alloy is evaluated in terms of resultant cutting force, machined surface roughness, and material removal rate (MRR) through a multi-objective optimization approach. Turning experiments were performed wi أکثر

In the present study, the machining performance of titanium grade-1 alloy is evaluated in terms of resultant cutting force, machined surface roughness, and material removal rate (MRR) through a multi-objective optimization approach. Turning experiments were performed with CVD-coated TiCN-Al2O3 carbide inserts using vegetable oil-based nanofluid under minimum quantity lubrication. The nanofluid was prepared using coconut oil as a base fluid mixed with boron nitride (hBN) nanoparticles. Experiments were performed by varying the cutting speed, feed, depth of cut, and nanoparticles concentration in a base fluid. The Desirability Function Approach (DFA), a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), and Non-dominated Sorting Genetic Algorithm (NSGA-II) are used to optimize the machining performance. The optimized solutions from different optimization techniques are observed in better agreement. The results show optimum performance at the higher cutting speed, higher depth of cut, lower feed, and lower concentration of nanoparticles. Lowest values for resultant force and surface roughness of 387 N and 0.47 µm, respectively, and maximum MRR of 9375 mm3/min could be obtained using the cutting speed, feed, depth of cut, and nanoparticles concentration of 125 m/min, 0.1 mm/rev, 0.75 mm, and 0.3%, respectively. However, little compromising the surface roughness to a higher value of 0.83 µm with almost the same resultant force, the higher MRR of 15000 mm3/min could be obtained using higher cutting parameters. It has been observed that the resultant force and surface roughness are significantly affected by the depth of cut and feed, respectively. However, the concentration of nanoparticles has been observed to have a lower prominent effect on the surface roughness and resultant force. تفاصيل المقالة

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16 - An Integrated Bi-Objective Mathematical Model for Minimizing Take-off Delay and Passenger Dissatisfaction
Razieh Larizadeh Reza Ramezanian

10.22094/joie.2021.1914607.1804

As air transportation has increased in recent years, it is necessary for airport planners to optimally manage aircraft ground traffic on stands, taxiways and runways in order to minimize flight delay and passenger dissatisfaction. A closer look at the literature in this أکثر

As air transportation has increased in recent years, it is necessary for airport planners to optimally manage aircraft ground traffic on stands, taxiways and runways in order to minimize flight delay and passenger dissatisfaction. A closer look at the literature in this area indicates that most studies have merely focused on one of these resources which in a macroscopic level may result in aircrafts’ collision and ground traffic at the airport. In this paper, a new bi-objective Mixed-Integer Linear Programming (MILP) model is developed to help airport management to integrate Gate Assignment Problem (GAP) and Runway Scheduling Problem (RSP) considering taxiing operation for departing flights. The proposed model aims to help airport planners to 1) minimize any deviation from preferred schedule and 2) minimize transit passengers’ walking distance. Due to the complexity of the research problem, a Normalized Weighted Sum Method (NWSM) is applied to solve small-sized problems and two meta-heuristics, namely NSGA-II and MOGWO, are used for large-scale instances to generate Pareto optimal solutions. The performance of these algorithms is assessed by well-known coverage and convergence measures. Based on the most criteria, the results indicate that MOGWO outperforms NSGA-II. تفاصيل المقالة

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17 - A New Model for Location-Allocation Problem within Queuing Framework
Seyed Hamid Reza Pasandideh Amirhossain Chambari

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be sp أکثر

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing framework. We formulate this model with two perspectives simultaneously: (i) customers and (ii) service provider. The objectives of the model are to minimize (i) the total expected travelling and waiting time and (ii) the average facility idle-time. This model represents a mixed-integer nonlinear programming problem which belongs to the class of NP-hard problems. In addition, to solve the model, two metaheuristic algorithms including non-dominated sorting genetic algorithms (NSGA-II) and non-dominated ranking genetic algorithms (NRGA) are proposed. Besides, to evaluate the performance of the two algorithms some numerical examples are roduced and analyzed with some metrics to determine which algorithm works better. تفاصيل المقالة

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18 - 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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19 - Optimal Location and Determination of Fault ‎Current Limiters in the Presence of Distributed ‎Generation Sources Using a Hybrid Genetic Algorithm
Salman Amirkhan Mostafa Rayatpanah Ghadikolaei Hassan Pourvali Souraki

Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. Due to the increasing need for electricity, the use of distributed generation sources in the power system is expanding rapidly. On the other ha أکثر

Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. Due to the increasing need for electricity, the use of distributed generation sources in the power system is expanding rapidly. On the other hand, in order to respond to the growth of load demand, the network becomes wider and more interconnected. These factors increase the level of fault current in the power system. Sometimes this increase causes the fault current level to exceed the ability to disconnect the protective devices, which can cause serious damage to the equipment in the power system. Using fault current limiters (FCLs) in power system is very promising solution in suppressing short circuit current and leads use of protective equipment with low capacities in the network. In this paper, in order to solve the problem of increasing the fault current, first using sensitivity analysis, network candidate lines are selected to install the fault current limiter, which helps to reduce the time and search space to solve the problem. Simultaneously finding the optimal number, location and amount of impedance for the installation of a resistive superconductor limiter is solved using the multi-objective Non-dominated genetic algorithm with non-dominated sorting (NSGA-II). The method presented in a 20 kV ring sample network, simulated in PSCAD software, is evaluated in the presence of distributed generation sources and its efficiency is shown. تفاصيل المقالة

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20 - An Approach Utilizing Epsilon-Constraint and NSGA-II for Circular Manufacturing Supply Chain Networks
Fatemeh Jaferi Arash Shahin Mohammadreza Vasili Omid Boyer Hassani

Circular manufacturing supply chains offer a novel and compelling perspective within the realm of supply chain sustainability. Consequently, the development of a suitable solution approach for circular manufacturing supply chains holds significant value. This study pres أکثر

Circular manufacturing supply chains offer a novel and compelling perspective within the realm of supply chain sustainability. Consequently, the development of a suitable solution approach for circular manufacturing supply chains holds significant value. This study presents appropriate solution approaches for a mathematical model that has been formulated for a circular supply chain. To address the small-sized problem, the epsilon-constraint method is proposed. This method aids in obtaining a Pareto set of optimal solutions, facilitating the evaluation of trade-offs among three objectives. Given the NP-hard nature of the problem, the non-dominated sorting genetic algorithm (NSGA-II) is employed to approximate the Pareto front for larger problem sizes. A comparative analysis is conducted between the outcomes achieved in smaller dimensions using the epsilon-constraint method and those generated by the metaheuristic algorithm. The results indicate that the error percentage of the objective function, when compared to the epsilon method, remains consistently below 1%, underscoring the effectiveness of the proposed algorithm. These methodologies empower decision-makers to offer efficient, optimal solutions, enabling them to select the most suitable alternative based on budgetary considerations and organizational policies. تفاصيل المقالة

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21 - طراحی و ساخت یک سیستم برودتی بهینه فتوولتاییک در حضور شبکه هوشمند با رویکرد بهینه‌سازی چند هدفه
رسول جوی زادگان مهدی مهدویان

امروزه بهینه سازی در سیستمهای قدرت یک ضرورت انکار ناپذیر است.کاهش شدت مصرف انرژی در تجهیزات الکتریکی و افزایش راندمان و کارایی آنها، کاهش تلفات الکتریکی و بهبود پروفیل ولتاژ در شبکه قدرت از نمونه های کاربرد بهینه سازی در سیستمهای قدرت می باشند. سیستمهای برودتی مانند یخچ أکثر

امروزه بهینه سازی در سیستمهای قدرت یک ضرورت انکار ناپذیر است.کاهش شدت مصرف انرژی در تجهیزات الکتریکی و افزایش راندمان و کارایی آنها، کاهش تلفات الکتریکی و بهبود پروفیل ولتاژ در شبکه قدرت از نمونه های کاربرد بهینه سازی در سیستمهای قدرت می باشند. سیستمهای برودتی مانند یخچالها و فریزر ها می توانند در کنار به کارگیری به همراه سیستمهای فتوولتاییک در شبکه قدرت عامل تعادل بخشی در عرضه و تقاضای انرژی الکتریکی باشند به طوری که مازاد انرژی را به صورت انرژی سرمایشی در خود ذخیره کرده و در شرایط لازم اجازه دهند که انرژی تولیدی توسط سیستم فتوولتاییک به شبکه قدرت تزریق گردد. در این مقاله به طراحی و ساخت یک سیستم برودتی (یخچال) فتوولتاییک متصل به شبکه و تنظیم بهینه عملکرد آن پرداخته شده است. توابع هدف هزینه و دمای میانگین یخچال به عنوان دو هدف اصلی در نظر گرفته شده و با به کارگیری الگوریتم بهینه سازی ژنتیک با مرتب سازی غیر مغلوب جوابهای پارتو به دست آمده و سپس با به کارگیری روش مدل جمع وزنی جواب نهایی انتخاب گردیده است. نتایج شبیه سازی با نرم افزار متلب و همچنین نتایج پیاده سازی سخت افزاری طرح پیشنهادی در غالب پروژه ساخت هر دو کارایی و عملکرد بهینه طرح پیشنهادی را تایید می نمایند. تفاصيل المقالة

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22 - ارائۀ یک مدل ریاضی برای زمان‌بندی تولید و تعمیرات و نگهداری با در نظر گرفتن محدودیت دسترسی به منابع تولیدی در شرایط عدم قطعیت
محمد شریف زادگان محمدرضا حیدری کورش پوری عادل پورقادر چوبر میلاد ابوالقاسمیان

10.30495/jmemiau.2023.706257

در سیستم های تولیدی و صنعتی، برنامه ریزی ادغامی تولید و عملیات و تعمیرات از اهمیت بسیار زیادی برخوردار است. از این رو در این پژوهش یک برنامه ریزی ادغامی چندهدفه با قابلیت بهینه سازی برای زمان‌بندی تولید و نگهداری و تعمیرات با ملحوظ دانستن محدودیت دسترسی به منابع تولیدی أکثر

در سیستم های تولیدی و صنعتی، برنامه ریزی ادغامی تولید و عملیات و تعمیرات از اهمیت بسیار زیادی برخوردار است. از این رو در این پژوهش یک برنامه ریزی ادغامی چندهدفه با قابلیت بهینه سازی برای زمان‌بندی تولید و نگهداری و تعمیرات با ملحوظ دانستن محدودیت دسترسی به منابع تولیدی در شرایط عدم قطعیت ارائه شده است. برای این منظور، یک مدل ریاضی برنامه ریزی مختلط عدد صحیح در راستای برنامه ریزی تولید و نگهداری و تعمیرات در شرکت مارون مدل سازی گردید. بر طبق نتایج حاصل شده، ماکزیمم سود حاصل شده پس از کسر هزینه‌ها برابر با 12690 میلیون دلار، کمترین ریسک ناشی از تولید محصول برابر با 3462 و کمترین مدت زمان اجرای نگهداری و تعمیرات برابر با 14172 ساعت محاسبه شده است. سرانجام، نتایج ارزیابی مدل سازی انجام شده نشان داد که استقرار نتایج حاصل از حل دقیق و فراابتکاری ارائه شده در این مقاله بیش از 7 درصد در تولیدات شرکت بهبود ایجاد می‌کند. تفاصيل المقالة

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23 - Feature Selection And Clustering By Multi-objective Optimization
Seyedeh Mohtaram Daryabari Farhad Ramezani

In this paper, feature selection and clustering is formulated simultaneously by using evolutional multi-objective algorithm. Archived multi-objective NSGA-II is hybridized with k-medoids algorithm to use global searching capabilities of GA with local searching capabilit أکثر

In this paper, feature selection and clustering is formulated simultaneously by using evolutional multi-objective algorithm. Archived multi-objective NSGA-II is hybridized with k-medoids algorithm to use global searching capabilities of GA with local searching capabilities of k-medoids for suitable centers of clusters and selecting suitable subset of features identifying the correct partitioning. Number of clusters should be determined as an input parameter by user. After determining number of clusters, archive string be generate randomly. In every solution of archived, center of clusters and features is determined. Objective functions are inter-cluster distance, intra-cluster distance and number of feature selection. Three objective functions are optimized simultaneously for partitioning and feature selection. Crossover and mutation operators are modified to solve the problem. In order to selecting final solution from pareto front, are modified to solve the problem is calculated. The Proposed algorithm were compared with other three clustering algorithms on seven UCI standard datasets and could improve results averagely 0.09 percent compared to FeaClusMoo, 0.28 percent compared to VGAPS-Clustering and 0.49 percent compared to K-means. تفاصيل المقالة

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24 - Minimizing the total tardiness and makespan in an open shop scheduling problem with sequence-dependent setup times
Samaneh Noori-Darvish Reza Tavakkoli-Moghaddam

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathe أکثر

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEAII. Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the traditional NSGA-II. تفاصيل المقالة

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25 - Multi-objective optimization of discrete time–cost tradeoff problem in project networks using non-dominated sorting genetic algorithm
Mohammadreza Shahriari

The time–cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving th أکثر

The time–cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving the project cash flow, avoiding unfavorable weather conditions, compensating the delays, and so on. Since there is a need to allocate extra resources to short the finishing time of project and the project managers are intended to spend the lowest possible amount of money and achieve the maximum crashing time, as a result, both direct and indirect costs will be influenced in the project, and here, we are facing into the time value of money. It means that when we crash the starting activities in a project, the extra investment will be tied in until the end date of the project; however, when we crash the final activities, the extra investment will be tied in for a much shorter period. This study is presenting a two-objective mathematical model for balancing compressing the project time with activities delay to prepare a suitable tool for decision makers caught in available facilities and due to the time of projects. Also drawing the scheduling problem to real world conditions by considering nonlinear objective function and the time value of money are considered. The presented problem was solved using NSGA-II, and the effect of time compressing reports on the non-dominant set. تفاصيل المقالة

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26 - TC-FLSFCL Provision for Improvement of Distribution System Reliability by TOPSIS based NSGA-II Method
Yashar Hashemi Khalil Valipour

An approach for assignment of the optimal location and tap changer adjustment related to flux-lock type superconducting fault current limiters with tap changer (TC-FLSFCL) is used in this paper by debating the reduction of fault current flowing from each device and enha أکثر

An approach for assignment of the optimal location and tap changer adjustment related to flux-lock type superconducting fault current limiters with tap changer (TC-FLSFCL) is used in this paper by debating the reduction of fault current flowing from each device and enhancement of reliability varying with customer type in a distribution network connected with distribution generation (DG). TC-FLSFCL is a flexible SFCL that it has some preference than previous SFCLs. In this type of SFCL the current limiting characteristics are improved and the fault current limiting level during a fault period can be adjusted by controlling the current in third winding, which also made the magnetic field apply to the high-Tc superconducting (HTSC) element. Three objective functions based on reliability index, reduction of fault current and number of installed TC-FLSFCL is systematized and non-dominated sorting genetic algorithm-II (NSGA-II) style is then formed in searching for best location and tuning of tap changer of TC-FLSFCL to meet the fitness requirements. A decision-making procedure based on technique for order preference by similarity to ideal solution (TOPSIS) is used for finding best compromise solution from the set of Pareto-solutions obtained through NSGA-II. In a distribution network as Bus 4 of Roy Billinton test system (RBTS), comparative analysis of the results obtained from application of the resistive SFCL (RSFCL) and TC-FLSFCL is presented. The results show that optimal placement of TC-FLSFCL than RSFCL can improve reliability index and fault current reduction index with less number تفاصيل المقالة

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27 - انتخاب سبد سهام بهینه با استفاده از الگوریتم ژنتیک NSGA-II
ابراهیم عباسی مهدی ابوالی مهدی سربازی

تشکیل سبد سهام بهینه یکی از تصمیم گیری های مهم برای شرکت ها می باشد. به همین دلیل، انتخاب یک سبد سهام با نرخ بازدهی بالا و ریسک کنترل شده یکی از موضوعاتی است که مورد توجه محققان قرار گرفته است. هدف از این پژوهش، استفاده از الگوریتم‌های فراابتکاری برای انتخاب سبد سهام اس أکثر

تشکیل سبد سهام بهینه یکی از تصمیم گیری های مهم برای شرکت ها می باشد. به همین دلیل، انتخاب یک سبد سهام با نرخ بازدهی بالا و ریسک کنترل شده یکی از موضوعاتی است که مورد توجه محققان قرار گرفته است. هدف از این پژوهش، استفاده از الگوریتم‌های فراابتکاری برای انتخاب سبد سهام است. در این مطالعه، روشی بر مبنای الگوریتم ژنتیک چند هدفهNSGA-IIبرای تشکیل سبد سهام ارائه شده و ارزش در معرض ریسک به عنوان معیار اندازه گیری ریسک مورد توجه قرار گرفته است. همچنین از داده های 50 شرکت برتر بورس اوراق بهادار تهران برای سال های 89-1385 استفاده شده است. نتایج نشان داد که الگوریتم ژنتیک چند هدفه می‌تواند جهت انتخاب سبد سهام بهینه بکار رود و عملکرد سبد طراحی شده توسط الگوریتم ژنتیک با عملکرد سبد سهام 50 شرکت برتر با اوزان مساوی تفاوت دارد. تفاصيل المقالة

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28 - ارائه مدل برنامه ریزی چندهدفه جهت انتخاب سهام با در نظرگرفتن ارزش در معرض خطر فازی: رویکرد تئوری اعتبار فازی
حسین دیده خانی سعید حجتی استانی

مسئله بهینه سازی پرتفوی و انتخاب سهام یکی از زمینه های پرتوجه توسط محققین مالی و سرمایه گذاران در بازارهای مالی می باشد. در این مقاله به برخی از چالش های بهینه سازی پرتفوی بطور همزمان پرداخته می شود. بطوریکه جهت در نظرگرفتن ماهیت چندمعیاره بودن انتخاب سهام و عدم قطعیت م أکثر

مسئله بهینه سازی پرتفوی و انتخاب سهام یکی از زمینه های پرتوجه توسط محققین مالی و سرمایه گذاران در بازارهای مالی می باشد. در این مقاله به برخی از چالش های بهینه سازی پرتفوی بطور همزمان پرداخته می شود. بطوریکه جهت در نظرگرفتن ماهیت چندمعیاره بودن انتخاب سهام و عدم قطعیت مرتبط با نرخ بازده دارایی ها از مدل برنامه ریزی چندهدفه فازی استفاده شد. همچنین با توجه نقاط ضعف معیارهای ریسک سنتی نظیر واریانس از ارزش درمعرض خطر و معیار عدم قطعیت با رویکرد تئوری اعتبار فازی جایگزین آن ها شدند. در پایان با توجه به ساختار غیرخطی و سخت مدل طراحی شده، از نسخه دوم الگوریتم ژنتیک چندهدفه با مرتب‌سازی نامغلوب "NSGA-II"، جهت حل مدل استفاده گردید. جهت نمایش قابلیت کاربرد مدل توسعه داده شده در بین 10 شرکت بین المللی بکارگرفته شد. پس از اجرای مدل و در راستای روایی سنجی، پرتفوی های پارتو بهینه بدست آمده با پرتفوهای تصادفی تولید شده مورد مقایسه قرار گرفتند. نتایج مقایسه نشان دهنده سطوح بالاتردستیابی به اهداف در پرتفوهای بهینه بود تفاصيل المقالة

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