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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 - A Smart Hybrid System for Parking Space Reservation in VANET
Farhad Rad hadi pazhokhzadeh hamid parvin -
Open Access Article
3 - An Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Hanieh Ghorashi Meghdad Mirabi -
Open Access Article
4 - 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
5 - 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
6 - Modeling and Comparison of Fuzzy and Non-Fuzzy Multi-Objective Evolution Optimization Portfolios in Tehran Stock Exchange
Mohammad Fallah Hadi Khajezadeh Dezfuli Hamed NozariSelecting the optimal stock portfolio is one of the most important issues in the field of financial research, which tries to choose the optimal combination of assets in order to create maximum utility for the investor, Given that the return on securities in the real wor MoreSelecting the optimal stock portfolio is one of the most important issues in the field of financial research, which tries to choose the optimal combination of assets in order to create maximum utility for the investor, Given that the return on securities in the real world is often vague and inaccurate, one of the most important investment challenges is uncertainty about the future. In this paper the problem of selecting and optimizing securities portfolios with different modeling goals has been solved and compared. The designed models have considered both the nature of the portfolio selection issue and the considerations considered by the shareholder in the portfolio selection. The uncertainty quality of the future return of a given portfolio is estimated using fuzzy LR numbers, while its return torques are measured using possibility theory. The most important purpose of this paper is to solve the problem and compare portfolio selection models with simultaneous optimization of two, three, and four objectives. For this purpose, the NSGA-II genetic algorithm is used and the mutation and intersection operators are designed specifically to generate possible solutions to the cardinality constraint of the problem. Finally, the efficiency and performance of the models in case of using fuzzy logic and not using it have been compared and it has been determined that the use of fuzzy logic and possibility theory leads to the formation of portfolios with higher performance and higher efficiency. Manuscript profile -
Open Access Article
7 - 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
8 - A box-uncertainty in multi-objective optimization: an ε-constraint approach
Shima Soleimani manesh Mansour Saraj Maryam Moemeni Mahmoud AlizadehIn the last few decades there has been lots of discussion in the literature regarding robust optimization. Since Epsilon constraint is one of the most important technique in interactive problems, therefore in this paper, due to the importance of robust optimization and MoreIn the last few decades there has been lots of discussion in the literature regarding robust optimization. Since Epsilon constraint is one of the most important technique in interactive problems, therefore in this paper, due to the importance of robust optimization and multi-objective programming problems, we consider Multi-Objective Linear Fractional Programming (MOLFP) problem in the presence of box-uncertainty in the coefficients of the objective functions. We propose an approach based on ε-constraint and Charnes-Cooper methods to obtain weakly robust efficient solutions, that have special importance in the literature, for a MOLFP problems in the presence of uncertain data. Charnes-cooper method is applied to reduce a fractional programm to a non fractional programm. At the end we write the robust counterpart of the UMOLFP model in the presence of the box-uncertainty and it's equivalent linear programming problem: Finally a numerical example is used to show the usefulness of the proposed approach. Manuscript profile -
Open Access Article
9 - 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
10 - Fuzzy multi-objective assembly line balancing problem: Fuzzy mathematical programming approach
A. Mahmoodirad S. Niroomand m. saneiDesign of assembly line is done in order to more coordinate a collection of some consecutive work stations for the aim of obtaining more productivity from the work stations and workers. The stations are arranged in a way to have a continuous and constant material flow. MoreDesign of assembly line is done in order to more coordinate a collection of some consecutive work stations for the aim of obtaining more productivity from the work stations and workers. The stations are arranged in a way to have a continuous and constant material flow. In this paper a multi-objective formulation for assembly line balancing is introduced. As a solution approach a two-step approach is proposed. In the first step the problem in a fuzzy environment is converted to a crisp problem and in the second step an efficient solution of the crisp problem is found by fuzzy programming approach. The efficiency of the proposed approach is shown by a numerical example. Manuscript profile -
Open Access Article
11 - A New Approach to Solve Fully Fuzzy Linear Programming with Trapezoidal Numbers Using Conversion Functions
S.H. NasseriRecently, fuzzy linear programming problems have been considered by many. In the literature of fuzzy linear programming several models are offered and therefore some various methods have been suggested to solve these problems. One of the most important of these problems MoreRecently, fuzzy linear programming problems have been considered by many. In the literature of fuzzy linear programming several models are offered and therefore some various methods have been suggested to solve these problems. One of the most important of these problems that recently has been considered; are Fully Fuzzy Linear Programming (FFLP), which all coefficients and variables of the problem are the same kind of fuzzy numbers. One of most common of them is the model in which all fuzzy parameters are discussed by triangle numbers. In this paper, we first define a fully fuzzy linear programming with trapezoidal numbers and then suggest a new method based on reducing the original problem to the problem with triangle number. Specially, a conversion function for converting two trapezoidal and triangular numbers to each other is offered. Finally, the mentioned method is illustrated by a numerical example. Manuscript profile -
Open Access Article
12 - A bi-level linear programming problem for computing the nadir point in MOLP
J. Vakili H. DehghaniComputing the exact ideal and nadir criterion values is a very ‎important subject in ‎multi-‎objective linear programming (MOLP) ‎problems‎‎. In fact‎, ‎these values define the ideal and nadir points as lower and ‎upper bounds on the MoreComputing the exact ideal and nadir criterion values is a very ‎important subject in ‎multi-‎objective linear programming (MOLP) ‎problems‎‎. In fact‎, ‎these values define the ideal and nadir points as lower and ‎upper bounds on the nondominated points‎. ‎Whereas determining the ‎ideal point is an easy work‎, ‎because it is equivalent to optimize a ‎convex function (linear function) over a convex set which is a convex optimization problem‎, ‎but the problem of computing ‎the nadir point in MOLP is equivalent to solving a nonconvex optimization‎problem whose solving is very hard in the general case‎. ‎‎In this paper‎, ‎a bi-level linear programming problem is presented for obtaining the nadirpoint in MOLP problems which can be used in general to optimize a ‎linear function on the nondominated set‎, ‎as well‎. Then‎, ‎as one of the solution methods of this problem‎, ‎a‎mixed-integer linear programming problem is presented which obtains ‎the exact nadir values in one stage‎. Manuscript profile -
Open Access Article
13 - A conjugate gradient based method for Decision Neural Network training
M. Nadershahi A. D. Safi Samghabadi R. Tavakkoli-MoghaddamDecision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available trai MoreDecision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore, decision makers can simply guess the necessary data. In this paper, for increasing the Decision Neural Network training efficiency, a conjugate gradient based method has developed for network training. The key point in decision neural network training is to keep the same structures and parameters of the two sub network (multilayer perceptron) through training process. The efficiency of the proposed method is evaluated by estimating linear and nonlinear utility function of multi-objective decision problems. The results of the proposed method are compared with previous existing method and show that in the proposed method, convergence is faster than previous methods and the results are more favorable. Manuscript profile -
Open Access Article
14 - A Compromise Decision-Making Model Based on TOPSIS and VIKOR for Multi-Objective Large- Scale Nonlinear Programming Problems with A Block Angular Structure under Fuzzy Environment
B. Vahdani M. Salimi T. AllahviranlooThis paper proposes a compromise model, based on a new method, to solve the multiobjectivelarge scale linear programming (MOLSLP) problems with block angular structureinvolving fuzzy parameters. The problem involves fuzzy parameters in the objectivefunctions and constra MoreThis paper proposes a compromise model, based on a new method, to solve the multiobjectivelarge scale linear programming (MOLSLP) problems with block angular structureinvolving fuzzy parameters. The problem involves fuzzy parameters in the objectivefunctions and constraints. In this compromise programming method, two concepts areconsidered simultaneously. First of them is that the optimal alternative is closer to fuzzypositive ideal solution (FPIS) and farther from fuzzy negative ideal solution (FNIS). Secondof them is that the proposed method provides a maximum ‘‘group utility’’ for the‘‘majority’’ and a minimum of an individual regret for the ‘‘opponent’’. In proposedmethod, the decomposition algorithm is utilized to reduce the large-dimensional objectivespace. A multi objective identical crisp linear programming derived from the fuzzy linearmodel for solving the problem. Then, a compromise solution method is applied to solve eachsub problem based on TOPSIS and VIKOR simultaneously. Finally, to illustrate theproposed method, an illustrative example is provided. Manuscript profile -
Open Access Article
15 - A Parametric Approach to Solving the Fuzzy Multi-Objective Linear Fractional Programming Problem
H. Naseri K. Khazaei kohparIn this paper a multi - objective linear fractional programming problem with the fuzzy variables and vector of fuzzy resources is studied and an algorithm based on a parametric approach is proposed. The proposed solving procedure is based on the parametric approach to f MoreIn this paper a multi - objective linear fractional programming problem with the fuzzy variables and vector of fuzzy resources is studied and an algorithm based on a parametric approach is proposed. The proposed solving procedure is based on the parametric approach to find the solution, which provides the decision maker with more complete information in line with reality. The simplicity of the proposed method is one of the advantages of the presented algorithm, which allows the decision maker to better understand the solving procedure. Moreover, a numerical example is presented to illustrate the proposed method. Manuscript profile -
Open Access Article
16 - 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
17 - 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
18 - 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
19 - Calculation of non-radial efficiency of decision-making units with fuzzy data using GDEA model
Atefeh Farshad Mohsen Rostamy-Malkhalifeh -
Open Access Article
20 - The approach of the goal programming to solve the problem of multi-criteria data envelopment analysis and its application in decision voting
Hamid sharafi -
Open Access Article
21 - Using Multi-Objective Linear Programming (MOLP) and Data Envelopment Analysis (DEA) models in Non-discretionary Performance Measurement
Sahar Khoshfetrat Mojtaba Ghiyasi -
Open Access Article
22 - Efficient Selection of Design Parameters in Multi-Objective Economic-Statistical Model of Attribute C Control Chart
S. Jafarian-Namin A. Amiri E. Najafi -
Open Access Article
23 - Measuring a Dynamic Efficiency Based on MONLP Model under DEA Control
K. Gholami Z. Ghelej Beigi -
Open Access Article
24 - 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
25 - Designing a Biodiesel Supply Chain Network by Considering Environmental FactorsUnder Uncertainty Conditions and solving it with the MOPSO algorithm
gholamreza jandaghi mohammad reza fathi mohammad hasan maleki Meysam MolaviBackground and Objective: Increasing concerns about energy and greenhouse gas emissions from fossil fuel consumption have encouraged many researchers to be involved in developing sources of renewable energies. Biodiesel derived from biomass can play a crucial role in th MoreBackground and Objective: Increasing concerns about energy and greenhouse gas emissions from fossil fuel consumption have encouraged many researchers to be involved in developing sources of renewable energies. Biodiesel derived from biomass can play a crucial role in this context. The main objective of this paper is to present a mathematical programming model for the biomass supply chain. Material and Methodology: Researcher through library research and preparing a questionnaire to estimate parameters and data associated with the uncertainty of parameters and then through interviews, expert opinions about the limits and changes to the decision-making parameters have collected. Then a fuzzy multi-objective mixed integer programming model is presented that model to minimize costs, minimize environmental impact and minimize the time of delivery of product in Biodiesel Supply Chain. Findings: After running the model, increasing objective function is to minimize the total cost, minimize environmental impact and minimizing the time the product reaches the customer contact temperature limits for different values were obtained. Discussion and Conclusion: In this study, the proposed mathematical programming model is solved with the MOPSO algorithm. The results indicate the location and capacity of the facility, the amount of biodegradable and glycerin production, and the amount of extracted Jatropha oil and refined waste oils. Manuscript profile -
Open Access Article
26 - Pond Designing Optimization Using Multi-ObjectiveAnt Colony Algorithm and SWAT Model
Abbas Afshar Mohammad Javad Emami Skardi Farzin JeiraniNon-point source management has an imperative role in water resource management. One of the most effective structures in the field of non-point source management is wet detention pond. However, generating the cost-effective pond configurations that satisfy system- MoreNon-point source management has an imperative role in water resource management. One of the most effective structures in the field of non-point source management is wet detention pond. However, generating the cost-effective pond configurations that satisfy system-wide aims for total target sediment removal will be much more effective and efficient; but most of these structures are designed individually. In order to generate the cost-effective pond configurations, coupling the optimization algorithm with hydrologic simulation model is one of the best applied methods. Materials and Method In this paper, an optimization-simulation model is presented for generating a cost-effective pond configuration in the watersheds. Obviously, more and larger ponds can catch more total suspended solids (TSS) from the watershed, but this will consequently lead to the increase of the cost of pond constructing. Multi-objective ant colony optimization algorithm is applied for determining a Pareto front between two opposing goals namely the loading TSS from the watershed and related cost of the pond designing. Result and Discussion The Pareto front can be used by the watershed authorities for a better controlling of the loading sediment from the watershed. The applicability of the model is studied in a watershed in the west of Iran. Manuscript profile -
Open Access Article
27 - Evolutionary multi-objective (3 or 4) optimization portfolio using fuzzy logic in Tehran Stock Exchange
Mohammad Javad Salimi Mirfeiz FallahShams Hadi Khajezadeh DezfuliThe problem of portfolio optimization and stock selection is one of the major areas for financial investors in financial markets. In this paper, some of the challenges of simultaneously multi-objective portfolio optimization are addressed. Four different models are desi MoreThe problem of portfolio optimization and stock selection is one of the major areas for financial investors in financial markets. In this paper, some of the challenges of simultaneously multi-objective portfolio optimization are addressed. Four different models are designed: a fuzzy multi-objective programming model has been used to consider the multi-criteria nature of stock selection and the uncertainty associated with the return on assets and a simple model for doing this. The models are designed in such a way that both the nature of the multiplicity of the problem of portfolio selection is considered and the considerations of the investor in the choice of portfolios are involved. After designing the evolutionary 3 and 4 objective models of portfolio optimization, multi-objective evolutionary algorithm NSGA-II was used to solve this models. Concretely, it optimizes return, the downside-risk, skewness and the Kurtosis of a given daily returns, taking into account budget, and investor constraints. Because of the NP-HARD nature of the above models, the NSGA-II proprietary algorithm was coded in the MATLAB, and after solving each model and extracting the Pareto frontier, the best portfolio on the Pareto front was selected based on the maximum Sortino ratio. Finally, the results of the obtained portfolios in both fuzzy and non-phase conditions were compared according to the trainer's ratio, and it was determined that the use of fuzzy logic in quadratic evolutionary algorithms, compared to a situation where fuzzy logic is not used in the design and use of these algorithms., Creates more favorable results. Manuscript profile -
Open Access Article
28 - Generalized Fuzzy Inverse Data envelopment Analysis Models
A. Ashrafi M. Mansouri -
Open Access Article
29 - Multi-Objective Model for Fair Pricing of Electricity Using the Parameters from the Iran Electricity Market Big Data Analysis
M. Salami F. Movahedi Sobhani M. S. Ghazizadeh -
Open Access Article
30 - 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
31 - رویکردی فازی برای حل مسایل برنامه ریزی کسری هندسی سیگنومیال چند هدفه عدد صحیح آمیخته
ژاله شیرین نژاد منصور سراج سارا شکراللهی فاطمه کیانیچکیدهاین مقاله روشی برای رسیدن به جواب بهین سراسری مسائل برنامه ریزی چند هدفه ی کسری هندسی (سیگنومیال)با متغیر صحیح آمیخته پیشنهاد می دهد . دراین مقاله نخست یک مسئله ی برنامه ریزی چندهدفه ی کسری هندسی(سیگنومیال) به وسیله ی یک راهبرد جدید وآسان به یک مسئله ی غیر کسری تبد Moreچکیدهاین مقاله روشی برای رسیدن به جواب بهین سراسری مسائل برنامه ریزی چند هدفه ی کسری هندسی (سیگنومیال)با متغیر صحیح آمیخته پیشنهاد می دهد . دراین مقاله نخست یک مسئله ی برنامه ریزی چندهدفه ی کسری هندسی(سیگنومیال) به وسیله ی یک راهبرد جدید وآسان به یک مسئله ی غیر کسری تبدیل می شودو برای رسیدن به جواب سراسری ازیک تبدیل ریلکس محدب استفاده می کنیم. سپس برای رسیدن به جواب صحیح بهین توافقی اهداف مسئله تکنیک های مرسوم برنامه ریزی فازی و نیزالگوریتم شاخه و کران غیر خطی را بکار می گیریم .علاوه براین برای یافتن جواب صحیح و سراسری با کوچکترین فاصله ازجواب مسئله ی اولیه از الگوریتم شاخه و کران فضایی استفاده می کنیم.در پایان برای نشان دادن درستی و کارایی راهبرد پیشنهادی دو مثال عددی ذکر شده است. Manuscript profile -
Open Access Article
32 - A new multi-mode and multi-product hub covering problem: A priority M/M/c queue approach
S. Sedehzadeh‎ R. Tavakkoli-‎Moghaddam‎‎ F. Jolai‎ -
Open Access Article
33 - Well-dispersed subsets of non-dominated solutions for MOMILP problem
SH. Razavyan -
Open Access Article
34 - A New Group Data Envelopment Analysis Method for Ranking Design Requirements in Quality Function Deployment
J. ‎Pourmahmoud‎ E. Babazadeh -
Open Access Article
35 - 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
36 - Pareto Optimum Design of Heat Exchangers based on the Imperialist Competitive Algorithm: A Case Study
Mohammadjavad Mahmoodabadi Soodeh Zarnegar -
Open Access Article
37 - 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
38 - 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
39 - 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
40 - Pareto Optimal Design of Passive and Active Vehicle Suspension Models
Mohammadjavad Mahmoodabadi Seyed Mehdi Mortazavi Yazdi -
Open Access Article
41 - 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
42 - Design an Adaptive Sliding Mode Controller for a Class of Underactuated Systems
Hossein Moeinkhah Mohammad Ahmadi Balootaki -
Open Access Article
43 - Minimum Stiffness and Optimal Position of an Intermediate Elastic Support to Maximize the Fundamental Frequency of a Vibrating Timoshenko Beam using Finite Element Method and Multi-Objective Genetic Algorithm
Hossein Ebrahimi Farshad Kakavand Hasan Seidi -
Open Access Article
44 - Multi-Objective Optimization of Plate Heat Exchangers by Employing an Imperialist Competitive Algorithm
Mohammadjavad Mahmoodabadi Soodeh Zarnegar -
Open Access Article
45 - An Optimal Routing Protocol Using Multi-Objective Cultural Algorithm for Wireless Sensor Networks (ORPMCA)
Seyed Reza Nabavi Mehdi Najafi -
Open Access Article
46 - Modeling and Analysis of SEPIC Converter Stability by Gray Wolf Multi-Objective Algorithm
Seyed Mohamad Naji Esfahani Seyed Hamid Zahiri Majid DelshadThis paper investigates the closed loop stability of the SEPIC converter using an optimal PID controller; In this model, the parameters are adjusted using the Gray Wolf Multi-Objective (MOGWO) algorithm. The Gray Wolf Multi-Objective Algorithm is a random evolution-insp MoreThis paper investigates the closed loop stability of the SEPIC converter using an optimal PID controller; In this model, the parameters are adjusted using the Gray Wolf Multi-Objective (MOGWO) algorithm. The Gray Wolf Multi-Objective Algorithm is a random evolution-inspired random algorithm that has been widely used in recent years as an optimization technique in power electronics. The state mode average method has been used to model and achieve the transducer-based system transfer function. Therefore, the MOGWO-based PID controller has been studied and implemented in the system to enable the converter stability to be evaluated and compared with conventional PID controllers. To evaluate the stability of the system, various performance parameters such as overtaking percentage, peak time, settling time and peak size have been considered. The impact response of the closed-loop system is obtained by simulation in MATLAB. The performance of the model is evaluated to perform a general comparative analysis of the system. Manuscript profile -
Open Access Article
47 - Reliability-Based Robust Multi-Objective Optimization of Friction Stir Welding Lap Joint AA1100 Plates
E Sarikhani A Khalkhali -
Open Access Article
48 - Constrained Multi-Objective Optimization Problems in Mechanical Engineering Design Using Bees Algorithm
A Mirzakhani Nafchi A Moradi -
Open Access Article
49 - Optimal Locations on Timoshenko Beam with PZT S/A for Suppressing 2Dof Vibration Based on LQR-MOPSO
M Hasanlu A Bagheri -
Open Access Article
50 - Using MODEA and MODM with Different Risk Measures for Portfolio Optimization
Sarah Navidi Mohsen Rostamy-Malkhalifeh Shokoofeh Banihashemi -
Open Access Article
51 - 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
52 - Optimization Bi Objective for Designing Sustainable Supply Chain Network Economic based Competition by Cost Management Approach
Reza Ehtesham Rasi -
Open Access Article
53 - Application of the two-stage DEA model for evaluating the efficiency and investigating the relationship between managerial ability and firm performance
Mohammad Reza Ravanshad Ali Amiri Hojjatallah Salari Davood Khodadadi -
Open Access Article
54 - 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 -
Open Access Article
55 - Making Decision on Selection of Optimal Stock Portfolio Employing Meta Heuristic Algorithms for Multi-Objective Functions Subject to Real-Life Constraints
Ali Sepehri Hassan Ghodrati Ghazaani Hossein Jabbari Hossein Panahian -
Open Access Article
56 - A new two-phase approach to the portfolio optimization problem based on the prediction of stock price trends
Hamid Reza Yousefzade Amin Karrabi Aghileh Heydari -
Open Access Article
57 - Fuzzy Compromise Approach for Solving Interval-Valued Fractional Multi-Objective Multi-Product Solid Transportation Problems
Hamiden Khalifa -
Open Access Article
58 - The Improvement of System Reliability Optimization Model and Finding an Optimal Solution
Seyed-Jafar Sadjadi Saeed Jafari -
Open Access Article
59 - Application of Genetic Algorithm for Optimization of Greenhouse Gas Emissions from Transport and cooling Supply Chain Costs
rasoul rezaei Davood Gharakhani Reza Ehtesham RasiThe cooling supply chain, due to its high energy consumption and refrigerant emissions, has high levels of greenhouse gas emissions and is one of the largest carbon emitters. In the cold supply chain, products should be stored at low and near or below freezing points. F MoreThe cooling supply chain, due to its high energy consumption and refrigerant emissions, has high levels of greenhouse gas emissions and is one of the largest carbon emitters. In the cold supply chain, products should be stored at low and near or below freezing points. For this purpose, refrigerated warehouses and refrigerated trucks are essential. Therefore, this research aims to design a linear multi-objective decision-making model for supply chain management Which aims to reduce the overall supply chain cost, including the cost of capacity, transportation, inventory as well as costs associated with the effects of global warming due to greenhouse gas emissions. To analyze the research problem, a mathematical model for optimizing the supply chain has been designed and genetic algorithm has been used to solve this problem. The results of the first function test indicate that the model is high in the number of customers, and when the distributor's number is equal to the number of producers, the best one is possible. The second function analysis concludes that reducing the restoration time of the facility is effective in minimizing the first function, reducing costs and reducing greenhouse gas emissions. Therefore, according to the stated contents and the results obtained in this research, it can be pointed out that by optimizing the vehicles and also the proper use of the optimal number of means of transport, it can be expected that the pollution and proliferation of gases The greenhouse is at least possible. Manuscript profile -
Open Access Article
60 - Closed loop supply chain network design under uncertainty
Reza Yousefi Zenouz Farzad Haghighi rad sajad zakeritabarClimate change and environmental impacts of economic activities, have forced supply chains to implement green policies and reduce environmental impacts and destruction to achieve competiete advantage. One approach to achive simultaneously to the economic and envitonment MoreClimate change and environmental impacts of economic activities, have forced supply chains to implement green policies and reduce environmental impacts and destruction to achieve competiete advantage. One approach to achive simultaneously to the economic and envitonmental objectives is to design closed loop supply chain networks (CLSCN) that integrate reverse logistics into their forward paths. In this paper, a bi-objective mixed integer linear programming model was developed for the CLSCN problem. The first objective is to minimize the cost function and the second objective function tries to minimize the time of transferring products from manufacturers to the distributors. Lp Metric and ε -constraint methods were utilized to solve the model. A numerical example was presented to show the applicability of the model and also sensitivity analysis was done. In this model two parameters of cost and demand are uncertain, in order to deal with uncertain parameters a robust optimization approach was utilizec. Multi objective particle swarm optimization (MOPSO) was used to solve the model in lare scales ad the solutions were compared with the solutions that obtained by exact methods. the findings of this research can help decision makers and executives to design efficient closed loop supply chains. Manuscript profile -
Open Access Article
61 - Designing a Multi-Objective Mathematical Model to Locate Four-Echelon Supply Chain Using Meta-Heuristic Algorithms
hamid Reza Mohammadi Reza Ehtesham Rasi Ali MohtashamiThe purpose of this paper is to design a multi-objective mathematical model in order to optimize the four-echelon supply chain of perishable goods using a hybrid algorithm with regard to procurement time, cost and customer satisfaction. Perishable four-echelon food supp MoreThe purpose of this paper is to design a multi-objective mathematical model in order to optimize the four-echelon supply chain of perishable goods using a hybrid algorithm with regard to procurement time, cost and customer satisfaction. Perishable four-echelon food supply chains are considered as different supply chains due to continuous and significant changes in the quality of food products throughout the chain until the end of consumption. In this research, a mathematical model for the location-routing facility in a four-echelon supply chain for perishable products with a simultaneous optimization approach of total supply chain costs, order delivery time, emissions and customer satisfaction is presented. To assess the validity of the research, the mathematical model in Behshahr food industry has been studied and the research problem is presented in the form of a multi-objective nonlinear programming model of mixed integer and to solve it, a hybrid of two refrigeration and red deer algorithms has been used. The results of the proposed algorithm are solved in a case study and the results of the algorithm performance are reviewed based on standard indicators and finally the computational results indicate the efficiency of the algorithm for a wide range of problems of different sizes. Manuscript profile -
Open Access Article
62 - Presenting a multi-objective mathematical model of multi-product and multi-stage fuzzy production planning for several periods in Gamz software
Aslan Doosti saeid Rezaie Moghadam saeid Rezaie MoghadamIn manufacturing and service processes, facing conditions of uncertainty and changes in the amount of data used in the model causes variable parameters, and therefore it is not uncommon to expect such conditions in decision making. Therefore, not paying attention to suc MoreIn manufacturing and service processes, facing conditions of uncertainty and changes in the amount of data used in the model causes variable parameters, and therefore it is not uncommon to expect such conditions in decision making. Therefore, not paying attention to such changes causes deviation in planning and deviation from the real situation and causes a lot of damage in the mentioned environments. Due to the importance of the issue, in this paper, the fuzzy optimization approach is used to deal with the uncertainty in the parameters of uncertainty of production stages and product quality in the manufacturer's center and model reconstruction center. The present study intends to design a mathematical model of a multi-objective production program and optimize it to minimize the cost of inventory, production, and manpower, and the maximum quality of the product and maximize the maximum occurrence of uncertainty at each stage of production that causes bottlenecks. It can increase the profitability of Borujen Concrete Parts Company. The results of solving the model by coding in Gamz software and using the comprehensive criterion method include the values of objective functions and decision variables. The results were approved by the officials of Borujen Stream Concrete Parts Company. Manuscript profile -
Open Access Article
63 - Solve the problem of time-cost-quality exchange of projects in the possible case by considering possible solutions
S. Farid Mousavi Kaveh Khalili-Damghani Farnaz Rezapour Arezoo Gazori-NishaboriTime-cost-quality trade-off project scheduling problem is one of the most important and practical problems in project management discipline. Project Managers interest in making decisions to accomplish the project with minimum cost, minimum time, and maximum quality. Unf MoreTime-cost-quality trade-off project scheduling problem is one of the most important and practical problems in project management discipline. Project Managers interest in making decisions to accomplish the project with minimum cost, minimum time, and maximum quality. Unfortunately, in real life problems, the estimation of time, cost, and quality may be mixed with uncertainty. These parameters may be far from their estimated values. So, considering uncertain parameters in time-cost-quality project scheduling is essential. In this paper, a probabilistic version of time-cost-quality trade –off problem is proposed. Some parameters of the proposed model are assumed to be probabilistic. The probabilistic nature of the proposed model is handled using stochastic chance constraint programming. The multi-objective nature of the problem is handled using goal programming. Finally, the stochastic chance constraint goal programming is proposed. The deterministic equivalence of proposed stochastic model is presented. A numerical example is analyzed using GAMS software and results are investigated. Manuscript profile -
Open Access Article
64 - Designing an Optimal Recycling Model in a Four-Level Closed-Loop Supply Chain by Queuing Theory and Robust Planning (Case Study: Paper Industry)
Mahdi Alizadeh Beromi Mohammad Ali Afshar Kazemi Mohammadali Keramati Abbass Toloie AshlaghiIn recent years, the growing industrial and economic competition, environmental concerns, and governmental pressures on manufacturers regarding waste management have underscored the significance of designing a reverse supply chain and closed-loop network. Simultaneously MoreIn recent years, the growing industrial and economic competition, environmental concerns, and governmental pressures on manufacturers regarding waste management have underscored the significance of designing a reverse supply chain and closed-loop network. Simultaneously, the potential for profit arising from product recycling has further emphasized the importance of these systems. This research focuses on developing a four-stage closed-loop network model for the supply chain, taking into account the uncertainty of product recycling rates. The primary objective of this study is to provide an integer linear programming model aimed at minimizing supply chain costs and customer service time under uncertain conditions. The supply chain model is designed by integrating queuing theory and product recycling system optimization. A critical aspect of this research involves modeling the uncertainty in the return rate of consumer products in the closed-loop supply chain, with the aim of developing a robust approach to address this issue. Additionally, the performance of the proposed model in the paper industry is evaluated, and a sensitivity analysis is conducted with respect to the decision variables using two metaheuristic algorithms: the Multiple Objective Harmony Search and the Non-dominated Sorting Genetic Algorithm. Manuscript profile -
Open Access Article
65 - The Solution of Multi-Objective Multimode Resource-Constrained Project Scheduling Problem with Multi-Objective Bees Metaheuristic Algorithm
Amir Sadeghi Sina Namazi Zahra Ghorajehlo Behnam RezvanpourResource Constrained Project Scheduling Problem (RCPSP) is the most general scheduling problem. Job shop scheduling, flow shop scheduling and other scheduling problems are the subsets of RCPSP. The present paper examines the multimode multi-objective resource-constraine MoreResource Constrained Project Scheduling Problem (RCPSP) is the most general scheduling problem. Job shop scheduling, flow shop scheduling and other scheduling problems are the subsets of RCPSP. The present paper examines the multimode multi-objective resource-constrained project scheduling problem (RCPSP) with partial precedence relations. To enhance the practical aspects of this prominent problem, important practical purposes including minimizing the completion time of the project, maximizing the quality of project activities and minimizing the total cost of the project were considered. After validation of the model using the Bees Algorithm, the proposed multi-objective model was solved. The results obtained from the proposed model were compared with those obtained from NSGA-II. The results demonstrated the good performance of the proposed algorithm in solving RCPSPs. Manuscript profile -
Open Access Article
66 - 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
67 - The Use of Fuzzy Multi-Objective Decision-Making Process to Provide Project Risk Assessment Model (Azar Oil Well Drilling)
Mohammad Reza Imani Moghadam Mohammad Khalil ZadehProject risk management in projects, illustrate the importance of risk ranking and prioritizing to focus more on the management of higher risk activities; in other words, activities are prioritized and ranked based on the risk of their performance.In this study, it has MoreProject risk management in projects, illustrate the importance of risk ranking and prioritizing to focus more on the management of higher risk activities; in other words, activities are prioritized and ranked based on the risk of their performance.In this study, it has been tried to use a multi-objective fuzzy planning in order to assess the potential risks of the project. To optimize these models, several objectives simultaneously are considered. The scale for each purpose may be different from the scale for the other purposes. In this model we have two aims: The first one is to minimize the expected cost of various risks and the second one is to minimize the expected time of the possible risks.A proposed method for a case study in Azar oil well drilling project in the region of Ilam is used. We have solved the model by the means of multi-objective decisions and LP metric. In LP metric method, we minimized the deviation in answers compared to ideal answer using the compatible functions and we changed the bi-objective model into single-objective one. Manuscript profile -
Open Access Article
68 - Multi-objective Portfolio Optimization Model by Fruit Fly Optimization Algorithm
Amir Amini alireza alinezhadOne of the most famous optimization problems in the field of financial engineering is portfolio selection problem. In its simplest form, while trying to minimize risk in the portfolio selection according to defined constraints such as budget and integer constraints it d MoreOne of the most famous optimization problems in the field of financial engineering is portfolio selection problem. In its simplest form, while trying to minimize risk in the portfolio selection according to defined constraints such as budget and integer constraints it deals with selecting a basket of various assets. Generally, investors prefer to invest in some assets rather than investing in only one asset to reduce unsystematic risk by diversifying their investment. Complex computational models have been developed to solve this problem and there is not an optimal solution for many of them. In this paper, a new and innovative approach known as fruit fly optimization algorithm (FOA) is used for multi-objective problem solving based on mean-variance Markowitz problem with class and cardinality constraints. Fruit fly optimization algorithm is a new way to find the overall optimal solution based on the behavior of the fruit fly in finding food. So far, few studies have been done on this algorithm and almost none of them used this algorithm for portfolio optimization problem. The results indicated the better comparative performance of the algorithm compared to the genetic algorithm for data set of Tehran stock exchange.JEL classification: G1, P5, O3 Manuscript profile -
Open Access Article
69 - A New Approach for Solving Multi-layered Facility Location Models under Uncertainty Using fuzzy Simulation
Mahdi Yousefi Nejad Attari Saeed Kolahi-Randji Ensiyeh Neyshabouri JamiDifferent systems have complex behaviors associated with the uncertainty of an important loss issue. Integration of discrete event systems in order to incorporate the uncertainty presented with the theory of fuzzy collections. Multi-layer facility location models have c MoreDifferent systems have complex behaviors associated with the uncertainty of an important loss issue. Integration of discrete event systems in order to incorporate the uncertainty presented with the theory of fuzzy collections. Multi-layer facility location models have complex behavior. In this model, customers receive different services in different layers addressing. The study seeks to provide a facility location models with multiple layers of serving and taking into account the density of the system. The proposed model is for a fuzzy nine linear programming model and it is placed in the field of highly complex issues. In order to solve the mathematical model, fuzzy simulation approaches have been used. In this regard, the applicant is to facilitate functions such as minimizing the travel and waiting time in the queue is the applicant. It is noted that after the implementation, the basic models and scenarios created and Arena software results of fuzzy been ranked. Manuscript profile -
Open Access Article
70 - 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
71 - 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
72 - An efficient algorithm for Volt/VAr control in distribution systems with distributed generation using binary ant colony optimization
reza azimi -
Open Access Article
73 - Presenting a Multi-Objective Mathematical Model for Designing a Logistics Network with Transfer Pricing and Transportation Cost Allocation: A Robust Optimization Approach
Sepideh Rahimi Behnam Vahdani -
Open Access Article
74 - An Approach to Reducing Overfitting in FCM with Evolutionary Optimization
Seyed Mahmood Hashemi -
Open Access Article
75 - A fuzzy hybrid approach for supplier selection and order allocation
Reyhaneh Hajati Majid Nojavan Davood MohammaditabarIn this paper, a new hybrid approach in supplier selection and order allocation is proposed. At the first step, the supplier evaluating criteria and sub-criteria are determined and their relationships and degrees of importance are specified via the fuzzy ANP-DEMATEL met MoreIn this paper, a new hybrid approach in supplier selection and order allocation is proposed. At the first step, the supplier evaluating criteria and sub-criteria are determined and their relationships and degrees of importance are specified via the fuzzy ANP-DEMATEL method. Afterwards, regarding the high variety of purchasing items, they are categorized into four groups by the Fuzzy Inference system (Kraljik model) and suppliers in each group are ranked using the Fuzzy WASPAS method. The next step is to determine the order allocation of items in a multi-product, multi-period, multi-supplier mixed integer programming model with three objectives of minimizing the cost, maximizing total utility of the purchasing process and minimizing changes of selected suppliers as a new objective function. Finally, the LP metric method is applied to solve the proposed multi-objective model, and Pareto solutions of the problem are determined by changing the coefficients of the objectives in this method. The proposed approach is used for suppliers evaluation and order allocation in a chemical company with a high number of purchasing items and suppliers. The accuracy of results is confirmed by experts. Regarding the comprehensiveness of the proposed approach, its application increases the accuracy of suppliers evaluation and order allocation, and therefore its utilization in organizations is recommended. Manuscript profile -
Open Access Article
76 - Presenting a goal programming model in Time-Cost-Quality trade-off problem in project management
Nima Hamta Mohammad Ehsanifar Javad SarikhaniThe time, cost and quality are important goals of each project, which project managers in order, to be succeed in the projects, always are looking for completion of them in the shortest possible time, with the lowest cost and highest quality. One of the main challenges MoreThe time, cost and quality are important goals of each project, which project managers in order, to be succeed in the projects, always are looking for completion of them in the shortest possible time, with the lowest cost and highest quality. One of the main challenges in this case is choosing the right approach to achieve these goals. The most common approaches in this case, are using the balance technique. In fact, using this technique can be the most optimal mode of project implementation activities that the lowest and highest quality at the lowest cost, time has obtained. In this paper, we tried to develop a goal-programming model to find suitable responses for managing the cost, time and quality of the project. In order to test this model, a case study was accomplished in the projects implemented at Company Machine Sazi Arak. Computational results show the applicability and usefulness of the proposed method. Manuscript profile -
Open Access Article
77 - Solving the multi-objective mathematical model of online load balancing in the production line with the Hybrid method of genetic algorithm and ant lion
Nima Rahmani Alireza Irajpour Naser Hamidi Akbar Alam Tabriz Reza Ehtesham RasiThe timely production of orders and their delivery to the customer is a competitive advantage that makes production systems and becomes customer satisfaction. Balancing the load of orders on work stations, reducing the time of the production period and minimizing the co MoreThe timely production of orders and their delivery to the customer is a competitive advantage that makes production systems and becomes customer satisfaction. Balancing the load of orders on work stations, reducing the time of the production period and minimizing the cost of human skills and access to machines can be components in the cases of balance of production lines. In this article, by addressing the above components of the mathematical model, several objectives for checking the online load balance are presented. Solving the mathematical model is done by introducing the combined meta-heuristic algorithm of multi-objective genetics and ant milk, this solution method selects the fittest parents based on the fitness of the initial population by using the feature of selecting the initial population and having the search memory to find quality answers at the right time. produces. The results obtained compared to the previous online load balancing methods show that the production time and load balance on the workstations have been improved. Manuscript profile -
Open Access Article
78 - Reducing the risk of Insolvency and costs in the field of banking with the approach of selecting partners
Moussa Azarbad Amirabbas Shojaie Farshid Abdi Vahidreza Ghezavati kaveh khalili DamqaniBanking is one of the main components of any system and government, and proper management and proper promotion are one of the key factors in the country's economic growth. Banks are exposed to multiple risks as well as lack of control over bank charges; in this regard, MoreBanking is one of the main components of any system and government, and proper management and proper promotion are one of the key factors in the country's economic growth. Banks are exposed to multiple risks as well as lack of control over bank charges; in this regard, appropriate strategies have to be adopted to improve banks' performance in this regard. One of these methods is the selection of partners to divide and reduce risk and share costs, so that they can reduce the Insolvency Risk of Banks and reduce the bank's share of cost control and lead to the bank's growth in financing and ultimately, economic growth in the country. In this research, a multi-objective model for selecting partners in the field of banking has been presented and further optimized using a multi-objective genetic algorithm.In this research, a multi-objective model for selecting partners in the field of banking has been presented and further optimized using a multi-objective genetic algorithm. Manuscript profile -
Open Access Article
79 - A Two-echelon Multi-objective Hybrid Model for Single-Vendor Multiple-Retailer Vendor Management Inventory Problem by using Two Pareto-based Multi-objective Meta-heuristic Algorithms
Mostafa Hoseinnezhadi Alireza IrajpurIn this research, a mathematical model for VMI is studied. One goal is to reduce inventory costs in a two-level supply chain, while other goals consider enabling the system and help making decisions in possible demand situations and delivery times, and increasing the le MoreIn this research, a mathematical model for VMI is studied. One goal is to reduce inventory costs in a two-level supply chain, while other goals consider enabling the system and help making decisions in possible demand situations and delivery times, and increasing the level of service and quality, while reducing the costs of increasing the service level. However, to gain more performance in real world problems, constraints exist, e.g. the lack of a low service level, warehouse space, budget, moving capacity, and total integrated discount. In this research, the shipments are assumed to be non-identical, and shortages are considered in two classes: lag and lost sales. Because the achieved model type is of nonlinear integer planning type and an NP-hard problem, meta-heuristic solutions should be used. Regarding two-goal minimization based on reducing total inventory cost, taking possible demand, delivery times, the non-homology of shipments into account, and also shortage and discount, to find the amount of product order and the product shortage level, the achieved model is solved using the required algorithms and tools. Regarding inventory management at two levels of seller and retailer, problems occur containing constraints. Finally, this research aims to obtain inventory management mathematical model by seller in the supply chain in conditions (such as one retailer-one seller, and one seller-multiple retailers), and to provide a solution during uncertainty, non-homology of shipments, when the shortage of lag and lost sales is permitted, and total discount. Manuscript profile -
Open Access Article
80 - EMCSO: An Elitist Multi-Objective Cat Swarm Optimization
Maysam Orouskhani Mohammad Teshnehlab Mohammad Ali Nekoui -
Open Access Article
81 - 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
82 - Fuzzy Multi-Objective Linear Programming for Project Management Decision under Uncertain Environment with AHP Based Weighted Average Method
Md. Sanowar Hossain Shahed Mahmud Md. Mosharraf Hossain -
Open Access Article
83 - Using NSGA II Algorithm for a Three Objectives Redundancy Allocation Problem with k-out-of-n Sub-Systems
mani sharifi Pedram Pourkarim Guilani mohammadreza shahriari -
Open Access Article
84 - Designing an integrated production/distribution and inventory planning model of fixed-life perishable products
Javad Rezaeian keyvan Shokoufi Sepide Haghayegh Iraj Mahdavi -
Open Access Article
85 - َA Multi-objective simulated annealing algorithm to solving flexible no-wait flowshop scheduling problems with transportation times
Bahman Naderi Hassan Sadeghi -
Open Access Article
86 - A Fuzzy Goal Programming Model for Efficient Portfolio Selection.
Abolfazl Kazemi Ali Shakourloo Alireza Alinezhad -
Open Access Article
87 - A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers
Parviz Fattahi Parvaneh Samouei -
Open Access Article
88 - A Bi-Objective Airport Gate Scheduling with Controllable Processing Times Using Harmony Search and NSGA-II Algorithms
Morteza khakzar Bafruei Sananz khatibi Morteza Rahmani -
Open Access Article
89 - Multi-Objective Optimization for Multi-Product Multi-Period Four Echelon Supply Chain Problems Under Uncertainty
Md Mashum Billal Md. Mosharraf Hossain -
Open Access Article
90 - Optimization of Multi-period Three-echelon Citrus Supply Chain Problem
Navid Sahebjamnia Fariba Goodarzian Mostafa Hajiaghaei-Keshteli -
Open Access Article
91 - An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation
Amir Hossein Azadnia Pezhman Ghadimi -
Open Access Article
92 - Bi-objective Optimization of a Multi-product multi-period Fuzzy Possibilistic Capacitated Hub Covering Problem: NSGA-II and NRGA Solutions
Zahra Rajabi Soroush Avakh Darestani -
Open Access Article
93 - Developing a New Bi-Objective Functions Model for a Hierarchical Location-Allocation Problem Using the Queuing Theory and Mathematical Programming
Parham Azimi Abulfazl Asadollahi -
Open Access Article
94 - Optimizing a bi-objective preemptive multi-mode resource constrained project scheduling problem: NSGA-II and MOICA algorithms
Javad Hasanpour Mohammad Ghodoosi Zahra Sadat Hosseini -
Open Access Article
95 - 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 -
Open Access Article
96 - Modelling and optimization of a tri-objective Transportation-Location-Routing Problem considering route reliability: using MOGWO, MOPSO, MOWCA and NSGA-II
Fariba Maadanpour Safari Farhad Etebari Adel Pourghader Chobar -
Open Access Article
97 - Multiple Items Supplier Selection, Economic Lot-sizing, and Order Allocation Under Quantity Discount: A Genetic Algorithm Approach
Getachew Basa Bonsa Till Becker Abdelkader Kedir -
Open Access Article
98 - Multi-objective optimization of production: A case study on simplex, goal programming, and pareto front models
Astrid Putri Mochamad Hariadi Reza Rachmadi -
Open Access Article
99 - A new approach to solving multi-follower multi-objective linear bilevel programming problems
Habibe Sadeghi Farzaneh Anis Hosseini -
Open Access Article
100 - Building a Multi-Objective Model for Multi-Product Multi-Period Production Planning with Controllable Processing Times: A Real Case Problem
Mir Bahadorgholi Aryanezhad Mehdi Karimi-Nasab Seyed Mohammad Taghi Fatemi Ghomi -
Open Access Article
101 - A Bi-objective Pre-emption Multi-mode Resource Constrained Project Scheduling Problem with due Dates in the Activities
zahra Sadat Hosseini Javad Hassan pour Emad Roghanian -
Open Access Article
102 - 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
103 - Multi-objective and Scalable Heuristic Algorithm for Workflow Task Scheduling in Utility Grids
Vahid Kahejvand Hossein Pedram Mostafa Zandieh -
Open Access Article
104 - Fuzzy Programming for Parallel Machines Scheduling: Minimizing Weighted Tardiness/Earliness and Flow Time through Genetic Algorithm
Mohammad Asghari Samaneh Nezhadali -
Open Access Article
105 - A multi-objective evolutionary approach for integrated production-distribution planning problem in a supply chain network
Keyvan Sarrafha Abolfazl Kazemi Alireza Alinezhad -
Open Access Article
106 - A Compromise Decision-making Model for Multi-objective Large-scale Programming Problems with a Block Angular Structure under Uncertainty
behnam vahdani meghdad Salimi behrouz Afshar najafi -
Open Access Article
107 - Application of Fuzzy Multi-objective Programming to Develop an Inventory Control Model
Mohammad Amin Nayebi Naser Hamidi Abbas Panahi niya Hesam SaediIn this paper, we presented the multi-item inventory control model whose objectives are minimizing total cost and minimizing the number of manpower. This model is formulated under four constraints consisting of storage spaces, budgetary, allowable shortage quantities an MoreIn this paper, we presented the multi-item inventory control model whose objectives are minimizing total cost and minimizing the number of manpower. This model is formulated under four constraints consisting of storage spaces, budgetary, allowable shortage quantities and periodic order quantities. The last two constraints are considered as interval. In the presented model, shortage is allowable and lead-time is zero. The parameters such as demands, costs (including: setting, maintenance, shortage) and constraint resources are fuzzy. The type of fuzzy numbers in demand & cost is triangular and the numbers of constraint resources are positive trapezoid. In solution methodology, first we converted the cost objective and manpower objective functions to six objective functions and then reduced fuzzy constraints to crisp constraints via defuzzification. Then we solved the resulted crisp multi objective model using Fuzzy Non Linear Programming (FNLP). Finally we presented a numerical example to solve and describe the model applying Lingo software package. Manuscript profile -
Open Access Article
108 - Designing an Incorporated Multi-Objective Green Supply Chain- Work Cost Model under non- Definitive Conditions
Mohammad ali ma.heydarisd manouchehr omidvari Zahra Valizadeh Ghareaghaji -
Open Access Article
109 - کاربرد الگوریتم ژنتیک چندهدفه (NSGA II)در انتخاب پرتفوی بهینه در بورس اوراق بهادار
سید احمد شیبت الحمدی محمد همتی مهدی اسفندیاردر موضوعات مالی سبد سهام را میتوان به معنی یک ترکیب و یا مجموعهای از سرمایه گذاریها دانست که بوسیله یک موسسه و یا یک فرد نگهداری میشود. بهینه سازی سبد سهام به منظور حداکثر سازی سود یکی از اصلی ترین دغدغههای سرمایه گذاران در بازارهای مالی است. تشکیل سبد سهام به عنوا Moreدر موضوعات مالی سبد سهام را میتوان به معنی یک ترکیب و یا مجموعهای از سرمایه گذاریها دانست که بوسیله یک موسسه و یا یک فرد نگهداری میشود. بهینه سازی سبد سهام به منظور حداکثر سازی سود یکی از اصلی ترین دغدغههای سرمایه گذاران در بازارهای مالی است. تشکیل سبد سهام به عنوان یک تصمیم گیری حساس و حیاتی برای شرکتها شناخته شده است. در واقع مسأله انتخاب سبد سهام مسأله تخصیص سرمایه بین گزینههای مختلف سهام می باشد. به همین دلیل انتخاب یک سبد سهام با نرخ بازدهی بالا و ریسک کنترل شده یکی از موضوعاتی است که مورد توجه بسیاری از محققان قرار گرفته است. روشهای فعلی در بهینه سازی سبد سهام از کارائی لازم برخوردار نبوده و لذا برای حل این مشکل الگوریتمهای ابتکاری مورد توجه قرار گرفته اند. الگوریتم ژنتیک یکی از الگوریتمهای ابتکاری است که میتواند مسائل بهینه سازی سبد سهام را با کارائی بالا انجام دهد. هدف تحقیق حاضر توضیح کامل الگوریتم ژنتیک و استفاده از این الگوریتم در مسائل بهینهسازی سبد سهام میباشد. مسأله انتخاب سبدهای سهام آن قدر پیچیده هستند که روشهای حل فعلی در برابر آن ناتوان بوده، از این رو استفاده از الگوریتمهای ابتکاری برای حل آنها مورد توجه قرار گرفته و توسعه یافته است. در این پژوهش روشی بر مبنای الگوریتم ژنتیک چند هدفه NSGA-II برای تشکیل سبد سهام ارائه می شود. همچنین ما دادههای 30 شرکت برتر را از شرکتهای بورس اوراق بهادار تهران به عنوان نمونه آماری انتخاب نموده و اطلاعات سهام آنها را از ابتدای سال 1386 تا پایان سال 1390 مورد استفاده قرار داده ایم. نتایج نشان می دهد که الگوریتم ژنتیک چند هدفه NSAG-II طراحی شده برای انتخاب سبد سهام ابزاری مناسب و کارا برای کمک به سرمایه گذاران در انتخاب سبد سهام میباشد. Manuscript profile -
Open Access Article
110 - 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 -
Open Access Article
111 - Multi-Objective Optimization for Coverage Aware Sensor Node Scheduling in Directional Sensor Networks
Nemat Mottaki Homayun Motameni Hosein Mohamadi -
Open Access Article
112 - A Mixed Integer Nonlinear Programming for Facility Layout Problem with Maintenance Constraints
Mehdy Morady Gohareh Ehsan Mansouri -
Open Access Article
113 - Improving the Efficiency of Actual Distribution System by Allocating Multi-DG and DSTATCOM
Masoud Alilou Sajad Sadi Saeed Zamanian Javad Gholami Shahab MoshariOptimal allocation of distributed generation units and DFACTS affects the efficiency of these devices; for this reason, in this article, the simultaneous placement of distributed generation and Distributed-STATic-COMpensator (DSTATCOM) are done in the distribution syste MoreOptimal allocation of distributed generation units and DFACTS affects the efficiency of these devices; for this reason, in this article, the simultaneous placement of distributed generation and Distributed-STATic-COMpensator (DSTATCOM) are done in the distribution system. The load model is considered as a combination of various customers’ daily load patterns and sensitive to voltage-frequency. The micro turbine, wind turbine, photovoltaic and fuel cell are considered as DG units. The objective functions of the problem consist of the technical index (the voltage stability and the active and reactive power loss) and environmental index (the amount of pollutant DG unit’s gas emissions). The whale optimisation algorithm (WOA) is used to multi-objective optimize the location and capacity of devices. After applying the multi-objective WOA, the analytical hierarchy process is utilized to select one of the Pareto optimal solutions as the best location and size of devices. The proposed algorithm is implemented on the 69-bus distribution system and actual 101-bus distribution system in Khoy–Iran. The results indicate the significant effect of load models and various DG units on the efficiency of the distribution system in the presence of DSTATCOM. Moreover, the indices of the distribution system are improved considerably after applying the proposed method. Manuscript profile -
Open Access Article
114 - Wireless Sensor Networks Routing Using Clustering Based on Multi-Objective Particle Swarm Optimization Algorithm
Seyed Reza Nabavi Nafiseh Osati Eraghi Javad Akbari TorkestaniWith the spread of applications of wireless sensor networks, in recent years, the use of this type of network in order to monitor the environment and analyze data collected from specific environments in a variety of ways has become very common. Wireless sensor networks MoreWith the spread of applications of wireless sensor networks, in recent years, the use of this type of network in order to monitor the environment and analyze data collected from specific environments in a variety of ways has become very common. Wireless sensor networks are one of the best options for collecting data from the environment due to their easy configuration and no need for expensive equipment. The energy of sensors in wireless sensor networks is limited, which is a major challenge due to the lack of a fixed charge source. Because most of the sensors' energy is wasted during data transmission, a sensor that transmits more data than others and transmits data over long distances with packets will run out of energy sooner than others. When a sensor in the network runs out of energy, the network process may be disrupted. Therefore, due to the dynamic topology and distributed nature of wireless sensor networks, designing energy efficient routing protocols is one of the main challenges. Therefore, in this article, energy-aware routing protocol based on multi-objective particle swarm optimization algorithm is presented. In the proposed approach, the fitness function of the particle swarm optimization algorithm for selecting the optimal cluster head based on quality-of-service goals including residual energy, link quality, end-to-end delay and delivery rate. The simulation results show that the proposed approach has less energy consuming and extend network lifetime due to balancing the goals of quality-of-service criteria than other approaches. Manuscript profile -
Open Access Article
115 - Dual-Objectives Energy and Load Management for an Energy Hub by Considering Diverse Plannings and in the Presence of CCUS Technology and the TOU Program
Fardin Niazvand Saeed Kharrati Farshad Khosravi Abdollah RastgouThis paper presents energy and load management by using a scenario-based assessment strategy for the optimal scheduling of a proposed hub by considering uncertain parameters (electricity price and wind turbine output power). Carbon capture utilization and storage (CCUS) MoreThis paper presents energy and load management by using a scenario-based assessment strategy for the optimal scheduling of a proposed hub by considering uncertain parameters (electricity price and wind turbine output power). Carbon capture utilization and storage (CCUS) technology and demand response programs (DRP), especially the time of use (TOU) program are investigated. Carbon technology helps to overcome pollution issues, on the one hand, and earn revenue for the power system, on the other hand. Also, the demand response programs help to reduce costs and pollution, make the load curve flatter, increase the reliability and power quality of the network. The proposed energy hub consists of various renewable and non-renewable distributed energy resources, as well different planning horizons, include deterministic and robust ones. The presented hub consists of diverse energy sectors like electricity, heat, cooling, gas, and water at the input and output sections. The problem is then modeled as a MILP and solved using the CPLEX solver in GAMS software. Epsilon constraint method with the fuzzy satisfying approach is used to obtain and select the best solution. The final results show that the cost and the pollution in the robust planning experience the increment by about 12.3% and 1.9% respectively in comparison to deterministic, as well, demand response programs and CCUS technology are had a significant impact on the objective functions. In addition, the load curve has become flatter and the reward by using a carbon system is obtained for the hub. Manuscript profile -
Open Access Article
116 - Presenting a Novel Hybrid Approach for Multi-Objective Distribution Feeder Reconfiguration Considering the Importance of Reliability
Benyamin Katanchi Ali Asghar Shojaei Mahdi YaghoobiSince it might delay making significant expenditures in substations and generation, increasing the efficiency of power systems is an important priority. By altering the status of switches, the distribution feeder reconfiguration (DFR) can reduce system losses in this re MoreSince it might delay making significant expenditures in substations and generation, increasing the efficiency of power systems is an important priority. By altering the status of switches, the distribution feeder reconfiguration (DFR) can reduce system losses in this regard. Power loss and voltage deviation of buses are frequently taken into account as objective functions while solving the distribution feeder reconfiguration problem, however reliability indices have received less consideration. The proposed reliability index, coupled with power loss and switching number in the presence of distributed generators, are used in this study to address DFR as a multi-objective problem. The DFR problem is complex inherently, considering impacts of distributed generators makes the problem more be complex than before. For this purpose, an evolutionary method based on the combination of particle swarm optimization and modified shuffled frog leaping has been used to solve the nonlinear optimization problem in this study. Two 33-bus and 70-bus systems are evaluated to gauge the effectiveness of the suggested hybrid algorithm. Manuscript profile -
Open Access Article
117 - A Novel Approach for Solving Linear Programming Problems with Intuitionistic Fuzzy Numbers
Ali Mahmoodirad -
Open Access Article
118 - MOEICA: بهینه سازی چند هدفه پیشرفته براساس الگوریتم رقابت استعماری
امیرعلی نظری علی دیهیمیدر این مقاله، یک الگوریتم رقابت استعماری (MOEICA) چند هدفه پیشرفته ارائه شده است. ساختار اصلی ICA ابتکاری به کاربرده می شوند در حالی که برخی رویکردهای جدیدی نیز توسعه یافته اند. به غیر از مرتب سازی غیر تحت سلطه و روش فاصله ازدحا Moreدر این مقاله، یک الگوریتم رقابت استعماری (MOEICA) چند هدفه پیشرفته ارائه شده است. ساختار اصلی ICA ابتکاری به کاربرده می شوند در حالی که برخی رویکردهای جدیدی نیز توسعه یافته اند. به غیر از مرتب سازی غیر تحت سلطه و روش فاصله ازدحام که به عنوان ابزار اصلی برای مقایسه و رتبه بندی راه حل استفاده می شود، یک رویکرد مقایسه کمکی که اختیار فازی نامیده می شود نیز گنجانیده شده است. این طرح جدید کشورهای بیشتری را برای شرکت در هدایت مردم به سمت مسیرهای جستجوی مختلف قادر می سازد. علاوه بر این بار محاسباتی الگوریتم با انجام فرایند مرتب سازی در هر تکرار قوی نیست اما در برخی از فواصل از پیش تعریف شده کاهش خواهد یافت. فراوانی که با در نظر گرفتن پارامترانتخابی کنترل می شود،علاوه بر این، بازآفرینی امپراتوری و امپریالیسم چندین بار در طول پیشرفت بهینه سازی، اکتشاف بهتر و شانس کمتری برای دام افتادن در بهینه محلی را تشویق می کند. دلیل شایستگی های الگوریتم بر روی پانزده توابع الگو در شرایط معیارهای عملکرد مختلف مورد آزمایش قرارگرفت. نتایج از طریق مقایسه NSGA-II و MOPSO نشان می دهد که MOEICA حل کننده چند هدفه موثر تر و قابل اعتماد با توانایی زیادی در مرز پارتو حقیقی برای آزمون عملکردها در این مقاله را پوشش می دهد. Manuscript profile -
Open Access Article
119 - یک مدل چند هدفه فازی برای مشکل مدیریت پروژه
سید مائده میرمحسنی سید هادی ناصریدر ایـن تحقیـق، مسـئله تصمیمگیـری مدیریـت پـروژه چنـد هدفه با اهـداف فازی و محدودیتهـای فـازی مـورد توجـه قـرار گرفتـه اسـت. مـا یـک رویکـرد آلفـا بـرش و دو روش مختلـف راهحـل برنامهنویسـی اهـدف فـازی بـرای حـل مسـئله تصمیمگیـری چنـد معیاره مدیریت پـروژه (MOPM) را در محی Moreدر ایـن تحقیـق، مسـئله تصمیمگیـری مدیریـت پـروژه چنـد هدفه با اهـداف فازی و محدودیتهـای فـازی مـورد توجـه قـرار گرفتـه اسـت. مـا یـک رویکـرد آلفـا بـرش و دو روش مختلـف راهحـل برنامهنویسـی اهـدف فـازی بـرای حـل مسـئله تصمیمگیـری چنـد معیاره مدیریت پـروژه (MOPM) را در محیطهـای فازی ایجاد میکنیـم. برنامهریـزی خطـی چندهدفـه فـازی تعاملـی (I-FMOL) و روشهـای وزندهـی جمعـی پیشـنهاد شـده برای حـل مسـئله تصمیمگیری چندهدفـه (PM) کـه در آن اطلاعـات فـازی بـا اسـتفاده از توابـع عضویـت خطـی (LMF) نشـان داده میشـود. روشهـای پیشـنهادی تلاشـی معقولانـه بـرای بـه حداقل رسـاندن کل هزینههـای پـروژه، زمـان کل تکمیـل و هزینههـای ریـز ریـز شـده کل و محدودیتهـای متعـددی مانند زمـان بین وقایـع i و j، زمان وقوع فعالیـت (I, j) و کل بودجـه سـرمایه اسـت . وزن معیارهـای هـر تابع هدف بر اسـاس درجـه اولویت پـروژه DM بـا تکنیک AHP-Fuzzy محاسـبه شـده. تجزیه و تحلیـل عملکرد با مجموعـهای از اندازههـای فاصله بـرای برنامهریـزی خطی چندهدفه فـازی تعاملی (I-FMOLP) وروشهـای راهحل وزندهی جمعی محاسـبه شـده که نشـاندهنده اهـداف و محدودیتهـای عـدم قطعیـت در مسـئله تصمیمگیـری PM بـا راه حـل ایـدهآل در یـک مطالعـه موردی صنعتی اسـت، مقایسـه میشـود. Manuscript profile -
Open Access Article
120 - ارائه مدلی جهت تخصیص سفارش به تأمینکنندگان در شرایط تخفیف حجمی
امیر امینی علیرضا علی نژاد بهزاد نوریزادانتخاب تأمینکننده یک مسأله تصمیمگیری چندمعیاره است که هم فاکتورهای کمی و هم فاکتورهای کیفی را شامل میشود. به منظور انتخاب بهترین تأمینکننده نیاز به برقراری موازنه میان فاکتورهای ملموس و غیر ملموسی است که برخی از آنها ممکن است با هم در تضاد باشند. هنگامی که شرایط تخ Moreانتخاب تأمینکننده یک مسأله تصمیمگیری چندمعیاره است که هم فاکتورهای کمی و هم فاکتورهای کیفی را شامل میشود. به منظور انتخاب بهترین تأمینکننده نیاز به برقراری موازنه میان فاکتورهای ملموس و غیر ملموسی است که برخی از آنها ممکن است با هم در تضاد باشند. هنگامی که شرایط تخفیف حجمی مطرح باشد، این مسأله قدری پیچیدهتر میشود، در این تحقیق یک مدل برنامهریزی چندهدفه جهت تخصیص سفارش به تأمینکنندگان در شرایط تخفیف حجمی ارائه گردیده است. این مدل در حالت چند محصولی، با در نظر گرفتن معیارهای چندگانه و با محدودیتهای ظرفیت تأمینکننده ارائه شده است. در این خصوص تأمینکنندگان تخفیفات قیمت را بر اساس حجم معامله پیشنهاد میدهند. الگوریتم حل مدل چند هدفه ارائه گردیده و این مدل با استفاده از یک مثال عددی نشان داده شده است. Manuscript profile -
Open Access Article
121 - On solving possibilistic multi- objective De Novo linear programming
Hamiden Khalifa -
Open Access Article
122 - 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
123 - الگوریتم بهینه سازی چندهدفه کرم شب تاب برای طراحی جانمایی کارگاه ساختمانی
Abolfazl Ghadiri داود صداقت شایگان علی اصغر امیرکاردوستاهمیت ایمنی در طرح چیدمان سایت ساخت و ساز یک نیاز ضروری برای بهبود مدیریت پروژه ساختمانی است. در مطالعات قبلی تابع هدف، ایمنی بدون تجزیه و تحلیل عوامل خطر در نظر گرفته شده است. فراابتکاری ها به طور گسترده ای برای حل مسائل برنامه ریزی چیدمان سایت ساخت و ساز استفاده می شو Moreاهمیت ایمنی در طرح چیدمان سایت ساخت و ساز یک نیاز ضروری برای بهبود مدیریت پروژه ساختمانی است. در مطالعات قبلی تابع هدف، ایمنی بدون تجزیه و تحلیل عوامل خطر در نظر گرفته شده است. فراابتکاری ها به طور گسترده ای برای حل مسائل برنامه ریزی چیدمان سایت ساخت و ساز استفاده می شود. الگوریتم کرم شب تاب (FA) به عنوان روش بهینه سازی چند هدفه برای طراحی و بهینه سازی دو تابع هدف ایمنی و هزینه کل استفاده می شود. توابع هدف ایمنی (به دلیل خطرات بالقوه ناشی از منابع خطرناک و جریان های متقابل) اتصال تأسیسات موقت با در نظر گرفتن کاهش هزینه کل. یک مطالعه موردی برای پی بردن به دقت مدل پیشنهادی ارائه شده است. در نهایت، عملکرد دو الگوریتم فراابتکاری به نامهای الگوریتم فایرفلای (FA) و بهینهسازی کلونی مورچهها (ACO) از نظر اثربخشی در حل مشکل طراحی سایت ساختوساز مورد مقایسه قرار گرفتهاند. نتایج نشان می دهد که FA بهتر از الگوریتم ACO عمل می کند. Manuscript profile -
Open Access Article
124 - Inverse DEA Model with Fuzzy Data for Output Estimation
A. محمودی راد ر. دهقان ف. حسین زاده لطفی -
Open Access Article
125 - Feature Selection And Clustering By Multi-objective Optimization
Seyedeh Mohtaram Daryabari Farhad Ramezani -
Open Access Article
126 - Devising a Profit-Aware Recommender System using Multi-Objective GA
Yaser Nemati Hossein Khademolhosseini -
Open Access Article
127 - 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
128 - An Efficient Three-Stage Yield Optimization Technique for Analog Circuits Using Evolutionary Algorithms
Abbas Yaseri Mohammad Hossein Maghami Mehdi Radmehr -
Open Access Article
129 - An Optimal Configuration of Neural Networks by Multi-Objective Genetic Algorithm and Ensemble-Classifier Approach for Evaluation Trust in the Single Web Service
baharak shakeri aski Abolfazl Haghighat mehran mohsenzadeh -
Open Access Article
130 - A Multi-Objective Decision-Based Solution for Facility Location-Allocation Problem Using Cuckoo Search And Genetic Algorithms
Amir Shimi Mohammad Reza Ebrahimi Dishabi Mohammad Abdollahi Azgomi -
Open Access Article
131 - Task Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
Mona Torabi -
Open Access Article
132 - تعیین الگوی کشت بهینه با هدف تصمیمگیری زیست-اقتصادی تحت شرایط عدم حتمیت
Mostafa Mardani Saman Ziaei Alireza Nikouei -
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133 - The sustainable supply chain of CO2 emissions during the coronavirus disease (COVID-19) pandemic
sina abbasi Maryam Daneshmand-Mehr Armin Ghane Kanafi -
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134 - Multi-objective design of fuzzy logic controller in supply chain
Mahdi Ghane Mohammad Jafar Tarokh Jafar Tarokh -
Open Access Article
135 - Combining data envelopment analysis and multi-objective model for the efficient facility location–allocation decision
Jae-Dong Hong Ki‑Young Jeong -
Open Access Article
136 - An L1-norm method for generating all of efficient solutions of multi-objective integer linear programming problem
Ghasem Tohidi Shabnam Razavyan -
Open Access Article
137 - Threshold F-policy and N-policy for multi-component machining system with warm standbys
Kamlesh Kumar Madhu Jain -
Open Access Article
138 - Constrained consumable resource allocation in alternative stochastic networks via multi-objective decision making
Seyed Saeid Hashemin Seyed Mohammad Taghi Fatemi Ghomi -
Open Access Article
139 - A multi-objective model for designing a group layout of a dynamic cellular manufacturing system
Reza Kia Hossein Shirazi Nikbakhsh Javadian Reza Tavakkoli-Moghaddam -
Open Access Article
140 - Multi-objective optimization of discrete time–cost tradeoff problem in project networks using non-dominated sorting genetic algorithm
Mohammadreza Shahriari -
Open Access Article
141 - A multiple objective approach for joint ordering and pricing planning problem with stochastic lead times
Zeinab Hosseini Reza Ghasemy Yaghin Maryam Esmaeili -
Open Access Article
142 - An optimization technique for vendor selection with quantity discounts using Genetic Algorithm
N Arunkumar L Karunamoorthy N Uma Makeshwaraa -
Open Access Article
143 - A full ranking method using integrated DEA models and its application to modify GA for finding Pareto optimal solution of MOP problem
S Razavyan GH Tohidi -
Open Access Article
144 - A weighted metric method to optimize multi-response robust problems
R Noorossana M Kamali Ardakani -
Open Access Article
145 - A fuzzy random multi-objective approach for portfolio selection
M.B Aryanezhad H Malekly M Karimi-Nasab -
Open Access Article
146 - Designing a multi-objective nonlinear cross-docking location allocation model using genetic algorithm
Ahmad Makui Laleh Haerian Mahyar Eftekhar -
Open Access Article
147 - An algorithm for multi-objective job shop scheduling problem
Parviz Fattahi Mohammad Saidi Mehrabad Mir B. Aryanezhad -
Open Access Article
148 - A fuzzy approach to solve a multi-objective linear fractional inventory model
S.J Sadjadi M.B Aryanezhad A Sarfaraz -
Open Access Article
149 - Lexicographic goal programming approach for portfolio optimization
H Babaei M Tootooni K Shahanaghi A Bakhsha -
Open Access Article
150 - Determining maintenance system requirements by viewpoint of availability and lean thinking: A MODM approach
S Ghayebloo H Babaei -
Open Access Article
151 - A multi-objective inventory model for deteriorating items with backorder and stock dependent demand
A.H Sarfaraz S Alizadeh Noghani S.J Sadjadi M.B Aryanezhad -
Open Access Article
152 - Multi-objective Dynamic Planning of Substations and Primary Feeders Considering Uncertainties and Reliability
Masoumeh Karimi Mahmoud Reza Haghifam -
Open Access Article
153 - 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
154 - Two-stage Framework for Microgrids Energy Management Considering Demand Response Program and Compressed Air Energy Storages under Uncertainties
Alireza Azarhooshang Sasan Pirouzi Mojtaba Ghadamyari -
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155 - A new hybrid algorithm for multi-objective distribution feeder reconfiguration considering reliability
hossein lotfi -
Open Access Article
156 - Multi-Objective Distribution Network Analysis Reconfiguration Considering Reliability of Power Supply based on Particle Swarm Optimization
Mostafa Karimi -
Open Access Article
157 - An Optimal Routing Protocol Using Multi-Objective Whale Optimization Algorithm for Wireless Sensor Networks
Seyed Reza Nabavi -
Open Access Article
158 - Per Unit Coding for Combined Economic Emission Load Dispatch using Smart Algorithms
Naser Ghorbani Ebrahim Babaei Sara Laali Payam Farhadi -
Open Access Article
159 - Wind Turbine Transformer Optimum Design Assuming a 3D Wound Core
Pedram Elhaminia Ahmad Moradnouri Mehdi Vakilian -
Open Access Article
160 - A Novel Model for Bus Stop Location Appropriate for Public Transit Network Design: The Case of Central Business Districts (CBD) of Tehran
Majid Jahani S. Mehdi Hashemi Mehdi Ghatee Mohsen Jahanshahi -
Open Access Article
161 - Designing of Fuzzy Multi-Objective (FMO) optimization model orientation integration of financial and operational flow in LARG supply network
Sina Aboei Mehrezi Mohammad Mehdi Movahedi Alireza Rashidi KemijanThe purpose of this article was to designing four level supply network with the simultaneous consideration of operational and financial flow in LARG supply network framework in Saipa Yadak Company. The innovation of article was presenting an integrated financial- operat MoreThe purpose of this article was to designing four level supply network with the simultaneous consideration of operational and financial flow in LARG supply network framework in Saipa Yadak Company. The innovation of article was presenting an integrated financial- operational approach to LARG supply network and new aspect of research was considering four levels of suppliers factories distribution centers and customers by Fuzzy Multi-Objective (FMO) optimization at strategic and technical decision-making levels. One of the prominent features of proposed model was use of Goal Programing (GP) for modeling financial flow and achieving producer's financial goals. Since the proposed model was a two objective model SO and TH FMO interactive approaches which are able to adjust degree of satisfaction of the objective functions were used to solve model. Using these approaches in addition to GP the enables decision-maker to make final decision by choosing the right solution based on degree of satisfaction and priority of each objective function. The mathematical model presented in the GAMS optimization software were coded and solved with CPLEX solver. Finally to show the efficiency and fit of the model integrated financial approach of the present article was compared with a non-financial model. Manuscript profile -
Open Access Article
162 - 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
163 - Stock portfolio optimization using multi-objective genetic algorithm (NSGA II) and maximum Sharp ratio
Arezou KarimiOne of the most important issues in finance is how to choose an investment portfolio. Activists in this field are seeking to select a portfolio that controls risk with high return. Due to the increasing limitations of the capital market, the efficiency of classical meth MoreOne of the most important issues in finance is how to choose an investment portfolio. Activists in this field are seeking to select a portfolio that controls risk with high return. Due to the increasing limitations of the capital market, the efficiency of classical methods has been discussed. Hence, researchers have turned their attention to metaheuristic algorithms. The aim of this study is to determine the optimal portfolio of pharmaceutical companies accepted in the Tehran Stock Exchange by two methods of multi-objective genetic algorithm (NSGA-II) and maximum Sharp ratio. In this study, the multi-objective genetic algorithm (NSGA-II) is under Conditional Value at Risk criterion. Also, the data of 13 companies in the period of 90-97 were used to form the portfolio. The results show that in the multi-objective genetic algorithm (NSGA-II) method, the stock with the lowest Value at Risk gains the most weight in the optimal portfolio. Also, the optimized portfolio by multi-objective genetic algorithm is more return and at the same time less risky. Manuscript profile -
Open Access Article
164 - Provide a multi-objective - multi-objective mathematical model for investing in a portfolio under a hybrid risk measure
ahmad dadashpour omrani syed ali nabavi chashmi erfan memarianWhat has been said so far in the financial calculations and in the field of stock portfolio selection is that it prioritizes the existing investments in terms of degree of risk and return, so that investors can, considering the financial possibilities and Their risk lev MoreWhat has been said so far in the financial calculations and in the field of stock portfolio selection is that it prioritizes the existing investments in terms of degree of risk and return, so that investors can, considering the financial possibilities and Their risk level to form their preferred stock portfolio. Therefore, in this research, to present a multi-objective mathematical model for measuring stock portfolio risk by combining return metrics with two risk metrics, namely half variance and conditional risk exposure value along with transaction cost limit for fifteen shares of the top fifty stocks. The period of twelve months ending in 1398 has been discussed in the context of the Iranian capital market. According to the tables and graphs obtained from solving this type of model with the help of dynamic planning in different investment times, we will see better results in the efficiency of investors' decisions by spending less time and money and consequently more profitability of the portfolio. Manuscript profile -
Open Access Article
165 - Stock portfolio optimization of companies listed on the Tehran Stock Exchange based on a combination of two-level ensemble machine learning methods and multi-objective meta-innovative algorithms based on market timing approach
sanaz faridi amir daneshvar Mahdi Madanchi Zaj Shadi ShahverdianiIn this article, using the market timing approach and homogeneous and inhomogeneous collective learning methods, the purchase, maintenance and sales signal and market forecast are presented based on the basic characteristics, technical characteristics and time series of MoreIn this article, using the market timing approach and homogeneous and inhomogeneous collective learning methods, the purchase, maintenance and sales signal and market forecast are presented based on the basic characteristics, technical characteristics and time series of returns of each company in the 100 days leading to the current day. . Based on this, 208 companies were selected as active companies between 1390 and 1399 To teach data by two-level ensemble learning machine (HHEL) and market trend forecasting based on market timing strategy, use data from 5 years 1390 to 1394 and to test the data as stock portfolio optimization based on stock portfolio maximization and risk minimization. The investment portfolio uses MOPSO and NSGA II algorithms and is compared with the obtained investment portfolio with the buy and hold strategy. The results showed that the MOPSO algorithm achieved the highest stock portfolio yield with 96.437% compared to the NSGA II algorithm with a yield of 91.157% and the same investment method with a yield of 13.058%. Also, the portfolio risk in NSGA II algorithm was much lower than the portfolio risk in MOPSO algorithm with 0.792% and 1.367%, respectively Manuscript profile -
Open Access Article
166 - Evolutionary 4-Objective Optimization Portfolio Algorithms for fuzzy and non-fuzzy selection
Mohammad javad Salimi Mohammad Taghi Taqhavi Fard Mirfeiz Fallahshams Hadi Khajezadeh DezfuliIn choosing the optimal portfolio, we must consider various criteria, some of which are determined by the nature of the optimization and some are determined by the investor's desire. Therefore, in this paper, multi-objective optimization models are designed and solved i MoreIn choosing the optimal portfolio, we must consider various criteria, some of which are determined by the nature of the optimization and some are determined by the investor's desire. Therefore, in this paper, multi-objective optimization models are designed and solved in MATLAB software environment. These models are designed in such a way that both the nature of the portfolio optimization, the considerations of the investor and the uncertain nature of the future return on assets, are taken into account. After designing the models in fuzzy and non-fuzzy (simple) conditions, due to their NP-HARD nature, a dedicated NSGA-II algorithm was used to solve it. After solving the models, the best portfolio from attained Pareto frontier, based on the Sortino ratio, be chosen. After that all of the obtained portfolios are compared according to the Treyner ratio. The results of statistical tests clearly show that the proposed models have a high power in choosing portfolios with maximum returns and a minimum risk. The results also indicate that that the designed models, with use of fuzzy logic in quadratic models creates more favorable results than simple models without using possibility theory and fuzzy logic. Manuscript profile -
Open Access Article
167 - Mining quantitative association rules with stock trading data using multi-objective Meta heuristic algorithms based on genetic algorithm
mostafa zandiyeh Sima MardanluForecasting stock return is an important financial subject that has attracted researchers’ attention for many years. Investors have been trying to find a way to predict stock prices and to find the right stocks and right timing to buy or sell. Recently, data minin MoreForecasting stock return is an important financial subject that has attracted researchers’ attention for many years. Investors have been trying to find a way to predict stock prices and to find the right stocks and right timing to buy or sell. Recently, data mining techniques and artificial intelligence techniques have been applied to this area. Association discovery is one of the most common Data Mining techniques used to extract interesting knowledge from large datasets. In this paper, we propose a new multi-objective evolutionary model which maximizes the omprehensibility, interestingness and performance of the objectives in order to mine a set of quantitative association rules from financial datasets, including 10 common indicators of technical analysis. To accomplish this, the model extends the two well-known Multi-objective Evolutionary Algorithms, Non-dominated Sorting Genetic Algorithm II and Non-dominated Ranked Genetic Algorithm, to perform an evolutionary learning of the intervals of the attributes and a condition selection for each rule. Moreover, this proposal introduces an external population and a restarting process to the evolutionary model in order to store all the nondominated rules found and improve the diversity of the rule set obtained. The results obtained over real-world stock datasets demonstrate the effectiveness of the proposed approach. Manuscript profile -
Open Access Article
168 - Presenting a fuzzy multi objective model for portfolio selection based on value at risk, semi-skewness and fuzzy credibility theory
Hosein Didehkhani Saeid HojjatiastaniIn finance, optimal portfolio selection, play's a crucial role for investor’s decisions. In practical cases the problem of optimal portfolio selection has some challenges. In a cases stocks are affected by various uncertain factors therefore, it is impossible to s MoreIn finance, optimal portfolio selection, play's a crucial role for investor’s decisions. In practical cases the problem of optimal portfolio selection has some challenges. In a cases stocks are affected by various uncertain factors therefore, it is impossible to simulate all of them properly. In this study, previous investigation about select and optimization of portfolio has been illustrated. For this purpose, credibility theory for calculating statistics moments such as Expected value, semi-skewness have been used. Also, the value at risk and Uncertainty is used for modeling in fuzzy Environment. For solving the model Matlab software run for solving Non-dominated sorting genetic algorithm "NSGA-II". And as result some of optimal pareto-front solutions have been obtained which were listed as optimal solution. To conclude Random portfolios has been created in order to compare with defined portfolios .the result indicate , defined models has more level of Satisfactory goals rather than Random portfolios. Manuscript profile -
Open Access Article
169 - An algorithm for determining common weights by concept of membership function
S. Saati N. Nayebi -
Open Access Article
170 - A Simple and Efficient Method for Solving Multi-Objective Programming Problems and Multi-Objective Optimal Controls
Hajar Alimorad -
Open Access Article
171 - A MODIFIED METHOD TO DETERMINE A WELL-DISPERSED SUBSET OF NON-DOMINATED VECTORS OF AN MOMILP PROBLEM
Ghasem Tohidi Shabnam Razavyan -
Open Access Article
172 - UNBOUNDEDNESS IN MOILP AND ITS EFFICIENT SOLUTIONS
G. Tohidi S. Razavyan -
Open Access Article
173 - Designing a Closed-loop Green Supply Chain in the Face of Competitive Demand and Product Pricing Simultaneously Using the Frog Jump Algorithm
Mojtaba Ramazani rasul nasrollahi saeedloIn this study, after a detailed and detailed review of past research in the field of supply chain, the research gap and its innovation were identified. The research innovation involved considering demand behavior as a function of product prices in competitive conditions MoreIn this study, after a detailed and detailed review of past research in the field of supply chain, the research gap and its innovation were identified. The research innovation involved considering demand behavior as a function of product prices in competitive conditions and based on that, the aim was to develop a mathematical model to design a closed loop supply chain in competitive conditions. In such a price chain, it is a fundamental factor that can determine the amount of demand and consequently change the structure of the chain. For this purpose, in the third chapter, first a function between the amount of demand and the price of products was presented. Then, by completing the research assumptions, a two-objective mathematical model of the research was presented. The first goal is to reduce costs and increase chain revenue. In other words, the first goal is to maximize supply chain profits. The second goal is to focus on market share, and by increasing the desirability of sales centers, we seek to maximize market share. By presenting such a model, it is necessary to provide techniques for achieving several goals. In this regard, the SFLA algorithm to solve this mathematical model was described. This method is a new meta-heuristic algorithm based on the behavior of frogs. For this purpose, first, by solving the model as a one-objective, the model was validated and the results were proved to be correct, logical and reliable. Manuscript profile -
Open Access Article
174 - 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
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