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Open Access Article
1 - Designing a mathematical model for the multi-product green supply chain of automobile industry under uncertainty
davood khodadadian reza radfar abbas toloieashlaghiToday supply chain network is recognized as the main bases in economic activity. Their significance is due to just in time delivery and the efficiency of different commodities including food, clothing, energy, computer hardware. This has stimulated researchers and exper MoreToday supply chain network is recognized as the main bases in economic activity. Their significance is due to just in time delivery and the efficiency of different commodities including food, clothing, energy, computer hardware. This has stimulated researchers and experts to analyze supply chain problems. Meanwhile, uncertainty has penetrated every level of our lives and we encounter it every day. The present paper focuses on green supply chain that consider uncertainty conditions to solve a model for designing a forward green supply network (environmental)under uncertainty of future economic conditions in Iran Khodro Company. The problem of designing the aforementioned network includes hypotheses including multi-commodity, multi-layer and one-period. Due to inconsistent economic conditions, uncertainty has been differently tackled here as compared with previous literature. In this problem, several important parameters have been considered as indefinite including customers’ demands, operating expenses, the productive capacity and relocating capacity of facilities. The proposed model also considers the contamination of production section and the transportation system of the chain and tries to reduce it by suggesting an objective function and Eco-indicator 99 method. As well, production and distribution centers operate in a dual-purpose manner. Saving costs and reducing contamination due to applying transportation supplies and common infrastructures are among the benefits of this method. Considering the complexity of solving this problem and its NP-hard nature, the meta heuristic method of genetic algorithm with non-dominated sorting (NSGAII) was analyzed and finally model performance was examined with a numerical example and solving it with MATLAB and GAMS software. Manuscript profile -
Open Access Article
2 - An Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Hanieh Ghorashi Meghdad Mirabi -
Open Access Article
3 - Sustainable closed-loop supply chain network design and operations planning considering human resource employment and training
R. Vakili Motie رضا Tavakkoli-Moghaddam A. Bozorgi-Amiri F. JolaiModeling and optimal solving of supply chain management problems lead to efficient decision making in strategic planning and supply chain operations, resulting in a competitive advantage. Today, with the planning of a sustainable supply chain, in addition to achieving e MoreModeling and optimal solving of supply chain management problems lead to efficient decision making in strategic planning and supply chain operations, resulting in a competitive advantage. Today, with the planning of a sustainable supply chain, in addition to achieving economic goals, it is possible to meet social and environmental objectives and considerations. This research deal with sustainable closed-loop supply chain network design and operations planning problem in which is human resource employment and training are considered. First, a three-objective optimization model is developed in which the supply chain network is designed and strategic variables (such as location and capacity determination, technology selection, skilled or semi-skilled employment and training, and etc.) are obtained. Then, a multi-period model is proposed supply chain operations planning in which the amount of production, inventory, shortage, temporary recruitment of manpower, etc. in each period are determined. In the proposed strategic model, a trade-off between the objectives of minimizing the cost of the supply chain (economic), maximizing employment (social), and minimizing environmental impacts is done by augmented epsilon constraint method. Also, Benders decomposition algorithm is used to solve large-scaled instances. In the final section of the research, some numerical studies are presented to provide numerical results, managerial insights and evaluating the performance of the proposed model and solution approaches. Manuscript profile -
Open Access Article
4 - An approach to find properly efficient solutions nearby ideal point in multi-objective optimization
Behnam Hozzar Ghasem Tohidi behrouz daneshianTrade-off between objective functions in multi-objective optimization is one of the tools for interpreting and studying efficient solutions. Properly efficient solutions are one of the most important theoretical and practical concepts that represent the behavior of the MoreTrade-off between objective functions in multi-objective optimization is one of the tools for interpreting and studying efficient solutions. Properly efficient solutions are one of the most important theoretical and practical concepts that represent the behavior of the objective functions during a process change. Actually, these solutions are those efficient solutions that filter the anomalies of objective functions at some points, and this will help the manager to decision making to choose more important solutions. One of the most important tools for obtaining solutions with bounded trade-off in multi-objective optimization field is the Sum weighted scalarization method, which many authors have been studying it in interactive optimization field. This paper provides a method for obtaining properly efficient solutions near the ideal point with a theoretical and interactive view and using Sum weighted scalarization method. Since being near to ideal point will be abele to a preference of decision maker; this method examines the preferences of the decision maker without sacrifice the theory. Therefore, this paper presents an approach to finding properly efficient solutions near to the ideal point. Manuscript profile -
Open Access Article
5 - Non-smooth Optimality for Robust Multi-objective Optimization Problems
Maryam Saadati Morteza OveisihaThis article is concerned with non-smooth/nonconvex robust multi-objective optimization problems involving uncertain inequality and equality constraints. Employing some advanced tools of variational analysis such as the approximate extremal principle and the weak fuzzy MoreThis article is concerned with non-smooth/nonconvex robust multi-objective optimization problems involving uncertain inequality and equality constraints. Employing some advanced tools of variational analysis such as the approximate extremal principle and the weak fuzzy sum rule for the Frechet subdifferential, we first drive a fuzzy necessary optimality condition of a non-smooth/nonconvex multi-objective optimization problem without any constrained qualification in the sense of the Frechet subdifferential. Then by exploiting the obtained fuzzy optimality condition, the non-smooth version of Fermat’s rule and formulae for the limiting subdifferential of an infinite family of non-smooth functions, we establish a necessary optimality condition in terms of the limiting subdifferential for weakly robust efficient solutions of the reference problem. Further,we present an example to illustrate this condition for an uncertain multi-objective optimization problem involving equality and inequality constraints.Finally sufficient conditions for weakly robust efficient solutions and robust efficient solutions of the problems are provided by presenting new concepts of generalized convexity. Manuscript profile -
Open Access Article
6 - A multi-objective optimization model for scheduling nurses and routing them in home health care services
Hamid Reza Yousefzadeh somayeh Harati Motlagh Moosarreza Shamsyeh ZahediRecently with the growing population and the consequences of factors such as the increase in the number of elderly and patients with chronic diseases, the demand for receiving Home Health Care (HHC) is increasing. HHC services providers are looking for the optimal solut MoreRecently with the growing population and the consequences of factors such as the increase in the number of elderly and patients with chronic diseases, the demand for receiving Home Health Care (HHC) is increasing. HHC services providers are looking for the optimal solutions in planning and scheduling HHC service delivery to maximize the satisfaction of patients and nurses in addition to minimizing the costs to patients. Accordingly on the one hand, the patients prefer to be visited at some specific periods based on their nursing skills. On the other hand, nurses are willing to provide services during their desired time windows. Following the rules corresponding to the working times in the contract, observing the soft and hard time windows, and taking required breaks are some of the restrictions that must be considered.The main objectives of this paper are to minimize the total traveling times and overtime of all nurses and to maximize the satisfaction level of patients as well as nurses, which are achieved through a multi-objective mathematical programming model.The proposed model considers the preferences of the nurses, as well as their patience. Moreover it establishes mandatory breaks for nurses after a certain period of work to assign qualified nurses to patients, optimize schedules, and determine the route of nurses, and provides high-quality services. Finally by applying the proposed model to a set of different random test problems, and by considering the stopping criterion on the problem solving time, we analyze the numerical results corresponding to optimal scheduling and allocation. Manuscript profile -
Open Access Article
7 - Evolutionary Multi-Objective Optimization for ultivariate Pair Trading in Tehran Stock Exchange: The Cointegration Approach
Hossein Nikoo jamal Barzegari Khanagha Hamid Reza MirzaeiPair trading strategy is one of the oldest and most common statistical arbitrage strategies. Pair formation is an important step in pair trading that examined manually and this method fails in the multivariate mode and does not consider conflicting goals in the problem MorePair trading strategy is one of the oldest and most common statistical arbitrage strategies. Pair formation is an important step in pair trading that examined manually and this method fails in the multivariate mode and does not consider conflicting goals in the problem structure. The main problem in this study is to present a method that creates multivariate pair combinations with multiple contradictory goals and focusing on the integration approach. Therefore, a combination of stocks optimized for two opposite objectives: risk (mean-reversion) and return (spread variance) to form a set of profitable multivariate pair trading opportunities. The statistical population is companies listed on the Tehran Stock Exchange. The statistical sample limited by the need for high-frequency transactions from the top 50 companies. The problem developed in the form of a mixed integer-programming model (MIP), and due to non-convex constraints and exponential space, a multi-objective genetic algorithm used to obtain pair combinations. To achieve multiple goals, an advanced type of genetic algorithm; The Chaotic Non-dominated Sorting Genetic Algorithm (CNSGA-II) was used. The Chaos theory used to create the initial population of the genetic algorithm in order to obtain appropriate and high-precision solutions. Research has shown that the use of chaos theory can increase the degree of convergence in evolutionary algorithms. The results of the experiments of this study show that multi-objective pair trading strategies focusing on the integration approach have a significant advantage over the traditional single-objective model. Manuscript profile -
Open Access Article
8 - Multi-Objective Optimization of Blood Products Supply Network to Minimize Delivery Time and Non-Estimated Hospital Demand
Zeinab Kazemi Mahdi Homayounfar mehdi fadaei Mansour Soufi Ali salehzadehIntroduction: Due to the importance of blood as a vital element in the health system, in this study, the blood supply chain is modeled at three levels of donors, banks (blood centers) and hospitals in the form of a multi-objective model to minimize total costs, total de MoreIntroduction: Due to the importance of blood as a vital element in the health system, in this study, the blood supply chain is modeled at three levels of donors, banks (blood centers) and hospitals in the form of a multi-objective model to minimize total costs, total delivery time of blood units and non-estimated demand of hospitals in each period.Methods: The present study is applied in terms of purpose and descriptive and quantitative in terms of method. The data needed to implement the real problem in 2021 have been collected by through the regional office of the Tehran blood transfusion organization along with the Negareh system. Due to the Np-hard nature of the problem, the proposed model is solved using three algorithms of GA, NSGA-II and MOPSO in GAMS software.Results: In the proposed model, matching the blood type in meeting demand; blood type delivery and allocation system in laboratories and blood banks, blood wasting in laboratory, transfer of products between demand centers, sensitive and determinative parameters of the model such as; demand, blood donation and delivery time of blood products between network components are considered indefinitely. The findings show that the MOPSO algorithm has a better performance in problems 3, 7, 10 and 12 for the QM index, but generally, based on running times and their average, the NSGA-II algorithm is better.Conclusion: Based on the results, the proposed model leads to a reduction in total costs, total delivery time of blood units and unapproved demand of hospitals. Manuscript profile -
Open Access Article
9 - Multi-Objective Optimization of Window Configuration to Provide Integrated Visual Comfort Components and Energy Efficiency by the Genetic Algorithm (The Case Study: Primary School Classroom in Tehran- Iran)
majid mofidishemirani firoozeh mohammadiMoving towards sustainable buildings requires more emphasis on accurate assessment of daylighting and energy performance. This is particularly important for educational buildings, because providing sufficient light while preventing the glare and reducing energy consumpt MoreMoving towards sustainable buildings requires more emphasis on accurate assessment of daylighting and energy performance. This is particularly important for educational buildings, because providing sufficient light while preventing the glare and reducing energy consumption in these spaces is a major challenge. In this article the main purpose is the optimized design of window configuration in terms of daylighting and energy performance in educational buildings (primary school classroom) in Tehran city to provide integrated visual comfort components (increase illuminance and decrease glare) and energy efficiency (reduced overall energy consumption). In the process of achieving this purpose the basic models of the South classroom were modeled parametricly by Grasshopper and dynamic simulation of daylight and energy was performed on them. Then simulation-based automated optimization process through the Genetic algorithm was accomplished in multi-objective.The results indicated that adjustment of the conditions with a higher weight for daylighting performance is necessary. The best Pareto solution, based on the minimum distance to the global optimum performs better than base model, indicating that improvements in UDI, DGP, and EUI purpose are 11, 15, and 22 percent respectively. Manuscript profile -
Open Access Article
10 - A multi-objective reservoirs system development as a sample case in the reservoir systems management
Samaneh Seifollahi-Aghmiuni Omid Bozorg-HaddadWater resources systems as a set of structures and equipment, strongly need proper operational programming in order to optimally supply demands and perform suitable water conservation. Water reservoirs are the most commonly used water resources systems for supplying dom MoreWater resources systems as a set of structures and equipment, strongly need proper operational programming in order to optimally supply demands and perform suitable water conservation. Water reservoirs are the most commonly used water resources systems for supplying domestic demands whose incorrect management may lead to unsuitable water resources protection and huge financial losses. Approximately in all of the reservoir design, operation and management problems, real reservoir system case studies are studied and analyzed according to the existing conditions and their objectives. Under these conditions, it can be very useful to define and introduce a sample reservoir system which can be investigated for all conditions and objectives. In this research, a three-reservoir system is presented for the first time, considering all physical and hydrological parameters beside three general objectives of generating hydropower energy, supplying downstream demands (agricultural, municipal and industrial) and flood control. The obtained results are quite logical, with a natural trend based on the logically defined data for the sample reservoir system. Therefore, this sample case study is capable of showing the performance of reservoir systems in different states of single or multi reservoirs and single or multi objectives. As a result, the presented reservoir system can be used as a sample case study for introducing and developing different methods in solving water reservoir system problems. Manuscript profile -
Open Access Article
11 - ارائه یک مدل زنجیره تامین سبز چندهدفه چندکالایی تحت شرایط عدم قطعیت
داوود خدادادیان رضا رادفر عباس طلوعی اشلاقیافزایش آلودگی زیستمحیطی که موجب گرم شدن کره زمین شده است و برای سلامت انسان و تخریب محیطزیست خطرناک است، باعث نگرانی بسیاری از طراحان و مدیران زنجیره تأمینشده است. هدف این پژوهش ارائه یک مدل ریاضی برای طراحی خرید، تولید و توزیع در یک شبکه زنجیره تأمین چند سطحی و چند Moreافزایش آلودگی زیستمحیطی که موجب گرم شدن کره زمین شده است و برای سلامت انسان و تخریب محیطزیست خطرناک است، باعث نگرانی بسیاری از طراحان و مدیران زنجیره تأمینشده است. هدف این پژوهش ارائه یک مدل ریاضی برای طراحی خرید، تولید و توزیع در یک شبکه زنجیره تأمین چند سطحی و چند محصولی است که تأثیرات زیستمحیطی و هزینههای کلی زنجیره تأمین به حداقل برساند و سطح رضایت مشتری به بالاترین سطح برسد. عدم اطمینان تقاضا به خاطر نامشخص بودن سطح تقاضا به نظر مشکلساز است. با توجه به پیچیدگی مدل ریاضی پیشنهادی و سختیهای حل مسئله با روشهای دقیق در اندازه بزرگ، یک NSGA II پیشنهادشده است. برای ارزیابی NSGA II پیشنهادی، 5 نمونه در اندازههای مختلف ساخته میشود و بهوسیله روش محدودیت اپسیلون و NSGAII حل میشود. بر اساس نتایج بهدستآمده، NSGA II پیشنهادی یک روش قابلاطمینان برای یافتن مرزهای پارتویی کارآمد در زمان قابلقبول محسوب میشود. Manuscript profile -
Open Access Article
12 - Improving Storage in Distributed Cloud Data Centers by Increasing Reliability Using Collective Intelligence Algorithms
Alireza Chamkoori Serajdean KatebiData security and privacy in data centers is an important issue. The major anxiety in security and privacy is the result of the fact that the topography of important operas can be available to sensitive information. To improve storage in distributed cloud data centers, MoreData security and privacy in data centers is an important issue. The major anxiety in security and privacy is the result of the fact that the topography of important operas can be available to sensitive information. To improve storage in distributed cloud data centers, the Particle Swarm Optimization (PSO) algorithm has been used to copy data between data centers. This paper summarizes the objectives and constraints of the cloud storage problem in order to achieve good performance by considering the shortest data transmission distance, obtaining optimal storage in distributed data centers with reliability based on PSO algorithm between two central data sets. And then it provides an intelligent cryptographic approach that cloud service operators cannot directly access partial data. Numerical results show that the proposed method can provide a good cloud storage strategy when the number of distributed data centers is equal, the defense of the main threats in the clouds can be done effectively. Manuscript profile -
Open Access Article
13 - Pareto Optimum Design of Heat Exchangers based on the Imperialist Competitive Algorithm: A Case Study
Mohammadjavad Mahmoodabadi Soodeh Zarnegar -
Open Access Article
14 - Design of Optimal PID, Fuzzy and New Fuzzy-PID Controller for CANSAT Carrier System Thrust Vector
A. Kosari H. Jahanshahi A. A. Razavi -
Open Access Article
15 - Finite Element Crushing Analysis, Neural Network Modelling and Multi-Objective Optimization of the Honeycomb Energy Absorbers
M. Vakili M. Farahani A. Khalkhali -
Open Access Article
16 - Optimal Robust Design of Sliding-mode Control Based on Multi-Objective Particle Swarm Optimization for Chaotic Uncertain Problems
Mohammadjavad Mahmoodabadi Milad Taherkhorsandi -
Open Access Article
17 - Pareto Optimal Design of Passive and Active Vehicle Suspension Models
Mohammadjavad Mahmoodabadi Seyed Mehdi Mortazavi Yazdi -
Open Access Article
18 - Multi-Objective Optimization of Loading Paths for Double-Layered Tube Hydroforming using Finite Element Analysis
Hamed Ebrahimi Keshmarzi Ramin Hashemi Reza Madoliat -
Open Access Article
19 - Multi-Objective Optimization of Plate Heat Exchangers by Employing an Imperialist Competitive Algorithm
Mohammadjavad Mahmoodabadi Soodeh Zarnegar -
Open Access Article
20 - Reliability-Based Robust Multi-Objective Optimization of Friction Stir Welding Lap Joint AA1100 Plates
E Sarikhani A Khalkhali -
Open Access Article
21 - Constrained Multi-Objective Optimization Problems in Mechanical Engineering Design Using Bees Algorithm
A Mirzakhani Nafchi A Moradi -
Open Access Article
22 - Uncertain Entropy as a Risk Measure in Multi-Objective Portfolio Optimization
Mahsa mahmoodvandgharahshiran Gholamhossein Yari Mohammad Hassan BehzadiAs we are looking for knowledge of stock future returns in portfolio optimization, we are practically faced with two principal concepts: Uncertainty and Information about variables. This paper attempts to introduce a pragmatic bi-objective investment model based on unce MoreAs we are looking for knowledge of stock future returns in portfolio optimization, we are practically faced with two principal concepts: Uncertainty and Information about variables. This paper attempts to introduce a pragmatic bi-objective investment model based on uncertainty, instead of probability space and information theory, instead of variance and other moments as a risk measure for portfolio optimization. Not only is uncertainty space expected to be more in line with investment theory, but also, applying and learning this approach seems more straightforward and practical for novice investors. The proposed model simultaneously maximizes the uncertain mean of stock returns and minimizes uncertain entropy as a measure of portfolio risk. The uncertain zigzag distribution has been used for variables to avoid the complexity of fitting distributions for data. This uncertain mean-entropy portfolio optimization (UMEPO) has been solved by three meta-heuristic methods of multi-objective optimization: NSGA-II, MOPS, and MOICA. Finally, it was observed that the optimal portfolio obtained from the proposed model has a higher return and a lower entropy as a risk measure compared to the same model in the probability space. Manuscript profile -
Open Access Article
23 - The Improvement of System Reliability Optimization Model and Finding an Optimal Solution
Seyed-Jafar Sadjadi Saeed Jafari -
Open Access Article
24 - Bi-Objective Hybrid Flow Shop Scheduling With Pareto Approximation in a Specified Region
Seyed Mostafa MousaviThis paper studies the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the maximum completion time and the total tardiness. In the past, bi-objective problems were solved by findin MoreThis paper studies the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the maximum completion time and the total tardiness. In the past, bi-objective problems were solved by finding Pareto approximation in the entire problem space (without any restrictions). The limitation in this study is to find Pareto approximation in a specified region. In order to solve the problem, multi-objective genetic algorithm based on Pareto ranking has been used. In the structure of the algorithm, two strategies have been proposed in order to select solutions for archiving and produce Pareto in a certain region. After generating sample problems, the genetic algorithm has been implemented with three strategies (two proposed and one general strategy in literature). The appropriate strategy is based on efficient solutions in the archives. The results reflect the fact that the proposed strategies have shown better performance than the literature strategy. Manuscript profile -
Open Access Article
25 - Optimization of the shell and tube heat exchanger with perforated quatrefoil plate using the meta-heuristic algorithms
seyed iman hashemi marghmaleki hadi eskandariIn this research, the thermal and hydraulic characteristics of the shell side of the shell and tube heat exchanger with perforated quatrefoil plate are optimized by a gray wolf and genetic algorithms in a single-objective multi-objective manner. The objective functions MoreIn this research, the thermal and hydraulic characteristics of the shell side of the shell and tube heat exchanger with perforated quatrefoil plate are optimized by a gray wolf and genetic algorithms in a single-objective multi-objective manner. The objective functions are heat transfer capacity for the maximum value and pressure drop for the minimum value. Shell and tube heat exchanger variables for optimization are: the diameter and number of tubes, the Reynolds number, the distance between baffles, and the height of the quatrefoil hole. The results show that for the maximum heat transfer of the quatrefoil baffle, the tube diameter is 0.03 m, the number of tubes is 30, The Reynolds number is 20000, the height of the perforated hole is 0.0018 m, and the distance between the baffles is 0.15 m. For the lowest pressure drop value, the diameter of the tubes is 0.03 m for the square arrangement and 0.01 m for the triangle arrangement; the Reynolds number is 5000, the height of the perforated hole is 0.003 m, and the distance between the baffles is 0.25 m. The optimization by the gray wolf and genetic algorithms has the same results for the shell and tube heat exchanger with a quatrefoil baffle. Manuscript profile -
Open Access Article
26 - The effect of the type of objective function to detect damage on the cracked beam clamped to multi-objective optimization methods
javad kheyroddin ehsan jamshidi alireza arghavanOne of the most important issues that is widely industry, monitoring the situation. To work with this system defects before he could create serious problem and known to tackle it. Damage in two ways: existent malicious and nondestructive and from where the solution with MoreOne of the most important issues that is widely industry, monitoring the situation. To work with this system defects before he could create serious problem and known to tackle it. Damage in two ways: existent malicious and nondestructive and from where the solution with less cost, so this method is more. One of the methods of identifying damage nondestructive ,methodology Modal parameters structure in this way is to investigate the changes Modal parameters, such as the natural frequencies and modes form before and after the damage to seek the site and levels of damage in are structures and damage to find with a wide range of response so a lot of research hit optimization techniques used in solving the problem for considering the dynamic parameters and changes in the structure that objective functions is considered to be optimized for them , and the amount of damage to the desired effectively The study by using the method of genetic algorithm to examine the structural damage, with regard to the presence of various target functions, first as a single point, and the accuracy of the response to the parameters for change in the algorithm sensitivity analysis, and then paid using various target functions and optimized genetic algorithm multi-purpose of the appropriate response is obtained. Manuscript profile -
Open Access Article
27 - An Approach to Reducing Overfitting in FCM with Evolutionary Optimization
Seyed Mahmood Hashemi -
Open Access Article
28 - Meta-heuristic Algorithms for an Integrated Production-Distribution Planning Problem in a Multi-Objective Supply Chain
Abolfazl Kazemi Fatemeh Kangi Maghsoud Amiri -
Open Access Article
29 - A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers
Parviz Fattahi Parvaneh Samouei -
Open Access Article
30 - Multi-Objective Optimization for Multi-Product Multi-Period Four Echelon Supply Chain Problems Under Uncertainty
Md Mashum Billal Md. Mosharraf Hossain -
Open Access Article
31 - A Simulated Annealing Algorithm for Multi Objective Flexible Job Shop Scheduling with Overlapping in Operations
Mehrzad Abdi Khalife Babak Abbasi Amirhossein Kamali Dolat abadi -
Open Access Article
32 - Multi-objective and Scalable Heuristic Algorithm for Workflow Task Scheduling in Utility Grids
Vahid Kahejvand Hossein Pedram Mostafa Zandieh -
Open Access Article
33 - Multi-Objective Optimization for Coverage Aware Sensor Node Scheduling in Directional Sensor Networks
Nemat Mottaki Homayun Motameni Hosein Mohamadi -
Open Access Article
34 - A Novel Approach for Solving Linear Programming Problems with Intuitionistic Fuzzy Numbers
Ali Mahmoodirad -
Open Access Article
35 - اندازه های کارایی متقاظع نامغلوب در تحلیل پوششی داده ها با رویکرد اهداف ثانویه
سعید شاه قبادی عباس قماشی فرهاد مرادیتحلیل پوششی داده ها (DEA) یک روش برنامه ریزی ناپارامتریک برای ارزیابی کارایی نسبی مجموعه ای از واحدهای تصمیم گیری متجانس (DMUs) با ورودی های متعدد و خروجی های متعدد است. روش کارایی متقاطع DEA روشی شناخته شده است که برای ارزیابی و رتبه بندی مجموعه ای از واحدهای تصمیم گیر Moreتحلیل پوششی داده ها (DEA) یک روش برنامه ریزی ناپارامتریک برای ارزیابی کارایی نسبی مجموعه ای از واحدهای تصمیم گیری متجانس (DMUs) با ورودی های متعدد و خروجی های متعدد است. روش کارایی متقاطع DEA روشی شناخته شده است که برای ارزیابی و رتبه بندی مجموعه ای از واحدهای تصمیم گیری متجانس استفاده می شود. هر زمان که یک DMU قصد ارزیابی سایر DMU ها را داشته باشد، با مشکل وزن های بهینه غیر یکتای مدل های DEA مواجه می شود. زیرا وزنهای مختلف امتیازات متقاطع متفاوتی را به ما میدهند و این باعث سردرگمی تصمیمگیرنده در تصمیمگیری نهایی میشود. اشکال اصلی این روش، مجموعه راه حل بهینه چندگانه است. هدف اصلی این مطالعه پیشنهاد رویکردی برای حل این مشکل برای ایجاد امتیازهای کارایی متقاطع DEA غیر غالب است. ما یک مدل هدف ثانویه برنامه ریزی خطی را برای انتخاب مجموعه ای از وزن های بهینه برای هر DMU پیشنهاد می کنیم. روش پیشنهادی ما نه تنها ساده تر از روش های دیگر ارائه شده با همین هدف است، بلکه کارایی بیشتری دارد. مثال های عددی برای نشان دادن این موضوع در پایان آورده شده است. Manuscript profile -
Open Access Article
36 - Feature Selection And Clustering By Multi-objective Optimization
Seyedeh Mohtaram Daryabari Farhad Ramezani -
Open Access Article
37 - An Improved Particle Swarm Optimization Algorithm for Energy Management in Distribution Grid Considering Distributed Generators
Hossein Lotfi Reza Ghazi Mohammad Bagher Naghibi Sistani -
Open Access Article
38 - An Efficient Three-Stage Yield Optimization Technique for Analog Circuits Using Evolutionary Algorithms
Abbas Yaseri Mohammad Hossein Maghami Mehdi Radmehr -
Open Access Article
39 - Task Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
Mona Torabi -
Open Access Article
40 - Multi-objective design of fuzzy logic controller in supply chain
Mahdi Ghane Mohammad Jafar Tarokh Jafar Tarokh -
Open Access Article
41 - Multi-objective Dynamic Planning of Substations and Primary Feeders Considering Uncertainties and Reliability
Masoumeh Karimi Mahmoud Reza Haghifam -
Open Access Article
42 - Fuzzy PID Tuned by a Multi-Objective Algorithm to Solve Load Frequency Control Problem
Ehsan Tehrani Amir Reza Zare Bidaki Mohsen Farahani -
Open Access Article
43 - A new hybrid algorithm for multi-objective distribution feeder reconfiguration considering reliability
hossein lotfi -
Open Access Article
44 - Multi-Objective Distribution Network Analysis Reconfiguration Considering Reliability of Power Supply based on Particle Swarm Optimization
Mostafa Karimi -
Open Access Article
45 - Multi-objective portfolio selection with multi-stage stochastic programming
Hamed Asgari javad BehnamianIn this paper, a multi objective multi stage stochastic model is proposed to portfolio selection. This model takes into account both the investment goal and risk control at each stage. A scenario generation method is proposed that acts as the basis of the portfolio mana MoreIn this paper, a multi objective multi stage stochastic model is proposed to portfolio selection. This model takes into account both the investment goal and risk control at each stage. A scenario generation method is proposed that acts as the basis of the portfolio management model. Scenarios for multistage portfolio management are proposed that use by consumption that rate of returns are not correlated during stages. One of the most important aspects of this model is using transaction cost in model and providing this ability that investors could add or withdrawal cash during time. In the end some numerical example are illustrated and model effectiveness proved. As is presented using stochastic programming with recourse and combination of this model with scenario generation model provides this possibility for investors to plan their medium and short term investing. As can be seen result of the model proved effectiveness of the model in financial markets. As result presented having such tool that investor could adjust his or her portfolio during time according to targets such as maximizing rate of return and minimizing risk of his or her decisions could bring powerful superiority in competitive financial markets. Manuscript profile -
Open Access Article
46 - Multi-Objective Optimization of the Depth and Cementation of Liquefiable Soil Surrounding Tunnels
Mohammad Shabani Soltan Moradi Mohammad Azadi Homayoun JahanianDesigning tunnels in liquefiable sandy soils presents a significant challenge in determining the optimal depth and extent of soil cementation around them. Reducing the depth of the tunnel decreases both the bending anchor force and the axial load on the tunnel's shell, MoreDesigning tunnels in liquefiable sandy soils presents a significant challenge in determining the optimal depth and extent of soil cementation around them. Reducing the depth of the tunnel decreases both the bending anchor force and the axial load on the tunnel's shell, yet it leads to an increase in ground surface settlement, and the opposite is true when depth is increased. Enhancing the cementation level at the tunnel's optimal depth reduces both structural uplift and shear forces exerted on the tunnel lining, but it also leads to an increase in axial loads and vice versa. Given the contradictory nature of these outcomes, the FLAC software was employed to simulate tunnels in liquefiable soils to address this dilemma. Subsequently, a neural network was utilized to identify correlations between the inputs and outputs of the simulation. This network was the objective function for identifying optimal values by applying a genetic algorithm. Optimal design parameters were derived using the NSGA-II modified algorithm, a multi-objective optimization technique based on the objective functions. Ultimately, Pareto charts generated from the multi-objective optimization process enabled designers to select the most suitable tunnel location according to their specific requirements concerning depth and soil cementation in liquefied soils. Manuscript profile