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Open Access Article
1 - Using the new meta-heuristic algorithm to determine the optimal capacity and location of electric car parking with the presence of renewable energy sources in the distribution system
Reza SedaghatiDue to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presenc MoreDue to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presence of electric vehicles as an additional load in the network can aggravate problems such as voltage drop, voltage stability and increase in network losses. In order to alleviate the effects caused by the uncontrolled presence of these cars, it is necessary to manage their required power in coordination with other dispersed production sources. Therefore, we should try to reduce losses by properly planning the charging and discharging of cars, along with scattered productions, having the right voltage and, as a result, better economic efficiency. Therefore, in this article, the optimal use of electric car parking lots with the presence of renewable energy sources in the distribution system has been studied. Optimization of the problem, a new meta-heuristic algorithm based on the flower pollination algorithm was used to determine the variables of the problem, including the optimal capacity and location of solar sources, as well as electric parking lots and diesel generators in the distribution network. The problem is subject to network operation restrictions (thermal line restrictions, network bus voltage restrictions, etc.), the number of cars in electric parking lots, the permitted power capacity of solar units, and the capacity of diesels have been optimized. In this study, the capability of the proposed method based on the flower pollination algorithm has been evaluated with other algorithms. The simulation was done on the distribution network of 33 IEEE buses, and the results show that the convergence speed and accuracy of the proposed method is high. Manuscript profile -
Open Access Article
2 - A survey of meta-heuristic methods for optimization problems
Mehdi FazliIn this article, we will examine the problems related to routing and positioning with real variables and examine the related questions. These engineering, inventory and optimization decisions are made in a multi-layered supply chain system, including suppliers, warehous MoreIn this article, we will examine the problems related to routing and positioning with real variables and examine the related questions. These engineering, inventory and optimization decisions are made in a multi-layered supply chain system, including suppliers, warehouses and different buyers. We are looking for new ways to manage location and routing efficiently and effectively. In order to increase efficiency and achieve optimal results, exploratory and meta-heuristic methods have been used. In meta-heuristic techniques, a combination technique is usually used to increase performance. Therefore, this review article examines meta-heuristic methods and analysis of location problems using different quantities. It also examines the advantages and disadvantages of each method to optimally solve these problems in order to introduce practical and efficient methods Manuscript profile -
Open Access Article
3 - Social Spider Optimization Algorithm in Multimodal Medical Image Registration
Zahra Hossein-Nejad Mehdi NasriMedical image registration plays an important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions. Multimodal medical image registration is the process of overlapping two or more images ta MoreMedical image registration plays an important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions. Multimodal medical image registration is the process of overlapping two or more images taken from the same scene by different modalities and different sensors. Intensity-based methods are widely used in multimodal medical image registration, these techniques register different modality images that have the same content by optimal transformation. The estimation of the optimal transformation requires the optimization of a similarity metric between the images. Recently, various optimization algorithms have been presented that the selection of appropriate optimization algorithms is very important in determining the optimal transformation parameter. The Social Spider Optimization (SSO) algorithm is one of the meta-heuristic methods that prevents premature convergence. In this paper, medical image registration technique is suggested based on the SSO algorithm. The Mutual Information (MI), Normalization of Mutual Information (NMI), and Sum of Squared Differences (SSD) are used separately as cost function (objective function) and the performance of each of these functions is checked in multimodal medical image registration. The simulation results on Brain Web data set affirm Manuscript profile -
Open Access Article
4 - Introducing a new meta-heuristic algorithm to solve the feature selection problem
Mehdi Khadem Abbas Toloie Eshlaghy Kiamars Fathi HafshejaniDue to the increase in the volume of data and information in recent years, the issue of choosing the most appropriate feature for decision making has become very important. Classic attribute selection methods cannot work well on big data. Because feature selection is a MoreDue to the increase in the volume of data and information in recent years, the issue of choosing the most appropriate feature for decision making has become very important. Classic attribute selection methods cannot work well on big data. Because feature selection is a complex problem, it seems appropriate to use meta-heuristic algorithms to solve this problem. In this paper, a new meta-heuristic algorithm inspired by nomadic migration to solve the feature selection problem is presented. This algorithm is named in honor of the Qashqai tribe. In this hybrid algorithm, the proportional function was designed based on the feature selection algorithm and based on minimizing the number of features and the amount of data error using neural network results. Then the Qashqai meta-heuristic algorithm was implemented on this fitness function and the results were compared with the well-known meta-heuristic algorithms of genetics and particle swarm. The results of the hypothesis test showed that the Qashqai optimization algorithm to solve the feature selection problem by the genetic algorithm and particle swarm is not defeated and in terms of convergence to the optimal solution works well. Manuscript profile -
Open Access Article
5 - A Novel ICA-based Estimator for Software Cost Estimation
Behrouz Sadeghi Vahid Khatibi Bardsiri Monireh Esfandiari Farzad Hosseinzadeh -
Open Access Article
6 - A Hybrid Intelligent Model to Increase the Accuracy of COCOMO
Vida Doranipour -
Open Access Article
7 - An Optimization-based Learning Black Widow Optimization Algorithm for Text Psychology
Ali Hosseinalipour Farhad Soleimanian Gharehchopogh mohammad masdari ALi Khademi -
Open Access Article
8 - Ranking Supply Chain Disruptions Using Mix Method, Fuzzy Dematel & Meta Heuristic Algorithms
fariba salahi reza radfar abbas toloie eshlaghi mahmood alborziAmong the types of supply chain risks disruptions are risks that resulting from natural disasters, sanctions, transportation problems and equipment failure. These risks can seriously disrupt the flow of materials, information and cash flow. This study proposes a hybrid MoreAmong the types of supply chain risks disruptions are risks that resulting from natural disasters, sanctions, transportation problems and equipment failure. These risks can seriously disrupt the flow of materials, information and cash flow. This study proposes a hybrid model for managing, evaluating and rating disorders. In this research, by presenting a mathematical model with disruption parameter, supply chain disruption risk assessment is investigated. Initially, the relationships between the disturbances are formulated by fuzzy DEMATEL technique, and the DEMATEL output as a weighted parameter, and then the model is solved using meta-heuristic algorithms, genetic and local search methods. Finally, the disruptions are evaluated and ranked based on the costs incurred in the chain, and then the number of appropriate suppliers for each disruption is determined. Manuscript profile -
Open Access Article
9 - Efficiency analysis of the meta-heuristic algorithms in portfolio optimization
Sina Shirtavani Mehdi Homayonfar Keyhan Azadi amir daneshvarThe most important goal of every investor in the stock market is to increase returns and reduce investment risk. Therefore, the purpose of this research is to analyze the effectiveness of meta-heuristic algorithms in stock portfolio optimization. Considering that in thi MoreThe most important goal of every investor in the stock market is to increase returns and reduce investment risk. Therefore, the purpose of this research is to analyze the effectiveness of meta-heuristic algorithms in stock portfolio optimization. Considering that in this research, the past performance of Tehran Stock Exchange companies is examined in past studies from 1390-1399, therefore, in terms of the research design, this research was post-event using Delphi and meta-analysis techniques. The statistical community of this research Academic researchers in the field of finance and active in the Tehran Stock Exchange, and the sampling method in this research was targeted with a volume of 30 people. The data collection tool was a researcher-made questionnaire. The method of collecting information was structured interview of researchers and review of the results of various studies in the field of determining the optimal stock portfolio in Tehran Stock Exchange. In order to analyze the data, Spss software version 23 and Laserl version 5.7 were used. The results showed that among meta-heuristic algorithms of genetic algorithm, ant colony and bee colony are the most suitable tools with the aim of not stopping at local optimal points and not premature convergence. Finally, after evaluating the appropriate algorithms, a comparison of the average risk and returns of the stock portfolio in genetic algorithms, ant colony and bee colony was done in the study unit, they showed that in terms of the criteria of reducing the risk of genetic and bee algorithms and in terms of increasing the return of the optimal portfolio Stock bee algorithm has worked more efficiently. Manuscript profile -
Open Access Article
10 - Designing Automatic Re-balancing Model Using Technical Analysis Concept of Divergence
S. M. Lale Sajjadi S. Hojjat Vakili S. Babak EbrahimiThe classical efficient market hypothesis states that it is not possible to beat the market by developing a strategy based on historical price series. In this paper we propose a profitable automatic trading system based on the divergence definition in relative strength MoreThe classical efficient market hypothesis states that it is not possible to beat the market by developing a strategy based on historical price series. In this paper we propose a profitable automatic trading system based on the divergence definition in relative strength index and using other technical analysis tools which presents empirical evidence confronting the classical efficient market hypothesis. In order to validate the developed solution an extensive evaluation was performed, comparing the designed strategy against the market itself and several other investment methodologies. An intraday database comprised of 59 symbols from NYSE in The time span 2010 to 2016 was employed. The whole sample is categorized over two sub-periods, training and widening its validity. By enjoying Meta-heuristic algorithms the rules in the first sub-period was improved. Then, in the second division the improved model was evaluated. The results indicates that this model improved predictability power and its performance is better than buy and hold and random strategies Manuscript profile -
Open Access Article
11 - Predicting negative stock price shocks based on the Meta heuristic approach
Ebrahim fadaei iman dadashi Mohammad javad zare bahnamiri kaveh azinfarAccording to capital market research, the negative shock of stock price in any market is a function of environmental factors and specific characteristics of the company and any insight into how to describe and predict the shock can influence the decisions of investors a MoreAccording to capital market research, the negative shock of stock price in any market is a function of environmental factors and specific characteristics of the company and any insight into how to describe and predict the shock can influence the decisions of investors and stakeholders. In this study, based on the data related to 96 financial ratios of 140 companies listed on the Tehran Stock Exchange during a period of 9 years between 2010 and 3012, we have predicted a negative shock of stock price based on the meta-heuristic approach. In this research, in order to extract the optimal financial ratios, genetic algorithms and particle swarm optimization have been used. The proposed model is then tested using these extracted features by a support vector machine with a radial core and an artificial neural network. The results showed that the variables extracted from the particle swarm optimization algorithm, together with the support vector machine learning algorithm, create better results for predicting shocks (temporary and permanent) and their number. Manuscript profile -
Open Access Article
12 - 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
13 - 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
14 - A novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model
Gholamreza Eslami Bidgoli Ehsan Tayebi SaniThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimi MoreThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimizing methodology differs. if we use Historical Simulation which is applied in this paper then the curve would be non-convex. On the other hand the Mean-VaR model here includes three sets of constraints: bounds on holdings, cardinality and minimum return which cause a Mixed Integer Quadratic Programming Problem. The first set of constraints guarantee that the amount invested (if any) in each asset is between its predetermined upper and lower bounds. The cardinality constraint ensures that the total number of assets selected in the portfolio’s equal to a predefined number. Because of above mentioned reasons, in this paper, we propose a new Meta-Heuristic approach based on combined Ant Colony Optimization (ACO) method and Genetic Algorithm (GA). The computational results show that the proposed Hybrid Algorithm has the ability to optimized Mean-VaR portfolio for small portfolio Manuscript profile -
Open Access Article
15 - Hybrid PSOS Algorithm For Continuous Optimization
A. Jafarian B. Farnad -
Open Access Article
16 - Optimum Design and Construction of Hydraulic Sections of Parabolic Water Transmitting Channels using the Harris Hawks Optimization Algorithm
Mehrzad torkzadeh Hamed Reza Zarif Sanayei reza kamgar -
Open Access Article
17 - Optimum Design of Solar Power Plant in Off-Grid Mode in Order to Reduce Construction Costs and the Amount of Unsupplied Load by ALPSO Algorithm
Layth Khudhair Abbas Halae Mohamadmahdi RezaeiSolar energy is the world's most unique and affordable renewable energy source and can be converted into many other forms. In this article, it will be discussed in a long-term perspective the technical and economic feasibility of installing stand-alone solar power plant MoreSolar energy is the world's most unique and affordable renewable energy source and can be converted into many other forms. In this article, it will be discussed in a long-term perspective the technical and economic feasibility of installing stand-alone solar power plant units with battery support to supply part of Baghdad's electricity. The objective function of this problem includes the cost of installation and maintenance of solar panels, batteries and inverter, which is solved with a certain interest rate in a 20-year perspective using IPSO and ALPSO methods. Furthermore, the load loss supplied and the charging/discharging limit are among the constraints. This article is unique in that it is implemented in the context of Baghdad city, and it also investigates the possible profit from selling power to main grid. Other features and innovations include the implementation of the new ALPSO algorithm. In this algorithm, the constraints of the problem are respected through a three-step adaptive search process. The results show that the proposed methods significantly reduce the lost load (especially in the ALPSO method), reduce the cost of maintenance and installation, and generally improve the performance of the system. Manuscript profile -
Open Access Article
18 - Comparison of Portfolio Optimization for Investors at Different Levels of Investors' Risk Aversion in Tehran Stock Exchange with Meta-Heuristic Algorithms
Mohammad Hassan Fotros Idris Miri Ayob Miri -
Open Access Article
19 - Support Vector Regression Parameters Optimization using Golden Sine Algorithm and Its Application in Stock Market
Mohammadreza Ghanbari Mahdi Goldani -
Open Access Article
20 - Application of meta-heuristic algorithms in portfolio optimization with capital market bubble conditions
Iman Mohammadi Hamzeh Mohammadi Khoshouei Arezo Aghaee chadeganiThe existence of bubbles in the market, especially the capital market, can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. On the other MoreThe existence of bubbles in the market, especially the capital market, can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. On the other hand, due to the goal of investors in achieving a portfolio of high returns with the least amount of risk, the need to pay attention to these markets increases. In this research, with the aim of maximizing return and minimizing investment risk, an attempt has been made to form an optimal portfolio in conditions where the capital market has a price bubble. According to the purpose, the research is of applied type, and in terms of data, quantitative and post-event, and in terms of type of analysis, it is of descriptive-correlation type. In order to identify the months with bubbles in the period from 2015 to 2021 in the Tehran Stock Exchange market, sequence tests and skewness and kurtosis tests were used. After identifying periods with bubbles, the meta-heuristic algorithms were used to optimize the portfolio. The results indicate the identification of 14 periods with price bubbles in the period under study. Also, in portfolio optimization, selected stock portfolios with maximum returns and minimum risk are formed. This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions. Manuscript profile -
Open Access Article
21 - A review of meta-heuristic methods for solving location allocation financial problems
Mehdi Fazli Somayyeh Faraji Amoogin -
Open Access Article
22 - Designing Prediction Model of Financial Restatements Using Neural-Genetic Simulation Algorithm
Sasan Mehrani Akbar Rahimi poorThe increased number of restatements in recent years has increased the wor-ries about the quality of financial reporting among the beneficiary groups. The pres-ence of prior period adjustments and, subsequently, the financial restatements have a negative impact on the r MoreThe increased number of restatements in recent years has increased the wor-ries about the quality of financial reporting among the beneficiary groups. The pres-ence of prior period adjustments and, subsequently, the financial restatements have a negative impact on the relatedness and reliability of the financial state-ments. The present study is aimed to present an appropriate criterion for predict-ing the financial restatements based on the Beneish model and its indices in companies admitted to the Tehran Stock & Exchange between 2009 and 2020. For this purpose, a total of 265 companies were selected considering the limitations. Also, the model estimation was per-formed using Beneish's primary model, a meta-heuristic neural network model, and optimization through genetic programming. As indicated by the obtained results based on the confusion matrix, the efficiency of the pro-posed model derived from the enhanced Beneish model with a genetic algo-rithm(S – 𝑆𝑐𝑜𝑟𝑒) had a total prediction accuracy of 73.21%, which was the highest prediction power compared to the Beneish Model . Manuscript profile -
Open Access Article
23 - Overview of Portfolio Optimization Models
Majid Zanjirdar -
Open Access Article
24 - بررسی عملکرد الگوریتم شاهین هریس در بهینهسازی مخزن سد
کبری رنجوری مهدی اژدری مقدم سید آرمان هاشمی منفرد سیما اوحدی در هر منطقه ­ای بر اثر کمبود نزولات جوی و با هر نوع آب و هوایی امکان رویداد پدیده خشکسالی وجود دارد. این پدیده به عواملی مانند دمای بالا، رطوبت نسبی پایین، ضریب پایین ذوب برف، باد و کمبود بارش بستگی دارد. بهره ­برداری بهینه مخازن با در More در هر منطقه ­ای بر اثر کمبود نزولات جوی و با هر نوع آب و هوایی امکان رویداد پدیده خشکسالی وجود دارد. این پدیده به عواملی مانند دمای بالا، رطوبت نسبی پایین، ضریب پایین ذوب برف، باد و کمبود بارش بستگی دارد. بهره ­برداری بهینه مخازن با در نظرگرفتن اهداف مهم چندگانه در کنار یکدیگر و بهصورت همزمان از اهمیت بالایی برخوردار است و به همین جهت لازم است حجم مخزن در هر ماه مدیریت شود؛ زیرا کارایی مخزن در کنترل سیلاب به حجم مخزن و مشخصات ژئومتری آن و سرریز بستگی دارد. در این مطالعه با استفاده از نرمافزار MATLAB و یک الگوریتم بهینه شاهین هریس دادههای سد امیرکبیر کرج به جهت یافتن میزان بهینه برداشت از مخزن سد، نوشته شد و الگوریتم شاهین هریس مورد ارزیابی قرار گرفت. الگوریتم مبتنی بر جمعیت، فرآیند جست­­جو را در دو مرحله اکتشاف و بهره­ برداری انجام میدهد. در الگوریتم شاهین هریس پارامترهایی وجود دارد که تغییر در مقدار آنها بر عملکرد این الگوریتم تأثیر می ­گذارد. در این مطالعه مقدار کمینه تابع هدف در الگوریتم شاهین هریس بررسیشد. با افزایش تعداد تکرارها، مقدار تابع هدف بهبود پیدا می ­کند و بهترین مقدار تابع هدف، در تکرار 64000 با مقدار 8934/25 بود که بهترین عملکرد الگوریتم در این تکرار بهدستآمد. Manuscript profile -
Open Access Article
25 - 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
26 - Comparing and Ranking of Meta-Heuristic Algorithms Using Group Decision Making Methods
Hojatollah Rajabi Moshtaghi Abbas Toloie Eshlaghy Mohammad Reza MotadelIn recent years, meta-heuristic algorithms and their application in solving complicated, nonlinear and NP-hard problems have dramatically increased, while new algorithms have constantly being introduced. In this research, with the aim of ranking meta-heuristic algorithm MoreIn recent years, meta-heuristic algorithms and their application in solving complicated, nonlinear and NP-hard problems have dramatically increased, while new algorithms have constantly being introduced. In this research, with the aim of ranking meta-heuristic algorithms, using group decision making techniques (different from other research in this field), 5 algorithms including: GA, PSO, ABC, SFLA and ICA by 15 standard test functions, and considering 2 attribute: "mean of answers" and "run time", have been compared. Then they are ranked by 3 group decision making methods including: "Cook and Seiford", "Condorcet" and "Dodgson". In addition, as in ranking by "Condorcet" and "Dodgson" methods, sometimes some options posit the same rank, therefore, in this study; we presented a proposal to overcome the limitation. Then the algorithms with these proposed methods were ranked. Finally, the overall ranking is done using an allocation model our results show that the overall ranking is as follows, respectively: PSO, ICA, GA, ABC and SFLA. Manuscript profile -
Open Access Article
27 - 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
28 - An Effective Frog-leaping Algorithm to Minimize the Completion Time Problem of the Resource-constrained Projects
Alireza Haji Akhondi Gholam Reza Tavakoli Peyman Akhavan Manouchehr ManteghiFrog leaping algorithm combination (SFLA) is an algorithm based on memetic Meta-heuristic. Created in recent years by Eusuff and Lansey, SFLA algorithm works in a way that the frog groups search for food. The development of memetic algorithms for local search method is MoreFrog leaping algorithm combination (SFLA) is an algorithm based on memetic Meta-heuristic. Created in recent years by Eusuff and Lansey, SFLA algorithm works in a way that the frog groups search for food. The development of memetic algorithms for local search method is similar to the activities of a frog among subgroups. SFLA uses a combination of strategy and provides the ability to exchange messages in local search. Frog leaping algorithm combines the advantages of particle swarm optimization algorithm and memetic development (PSO). Since the resource-constrained project scheduling problem is the timing issue, scheduling issues in the construction sites and plants is highly considered. One of the main duties of the project scheduling and project management is to reduce the completion time. Because of the resource constraints and precedence relationships between activities, project scheduling problem is difficult. In this paper, the algorithm performance LeapFrog (SFLA) is applied to reduce the project scheduling problems with resource constraints. The findings prove the robust performance of the new meta-heuristic algorithm. Manuscript profile -
Open Access Article
29 - Optimizing of Open Vehicle Routing Problem by Using an Efficient Hybrid Meta-heuristic Algorithm
Majid Yousefi khoshbakht Hassan Zarie Zahra Sadati Eskandari Narges Mahmmudi Daranie Ahmad Mahmmud JanloThe Open Vehicle Routing Problem (OVRP) is one of the most intensively studied problems in computational mathematics that nowadays and it has been receiving much attention by researchers and scientists. In this Problem, the objective is to define minimized distance trav MoreThe Open Vehicle Routing Problem (OVRP) is one of the most intensively studied problems in computational mathematics that nowadays and it has been receiving much attention by researchers and scientists. In this Problem, the objective is to define minimized distance traveled of the several vehicles that start to move simultaneously from the depot and visit some customers. It is noted that against to the Vehicle Routing Problem (VRP), it is not necessary that vehicles return to the depot after servicing the customers. This paper proposes a meta-heuristic algorithm in which at the first stage, a modified elite ant colony (EAS) is applied for finding a suboptimal solution, and at the second stage, the insert and swap local search algorithms are used for finding better solutions. Computational results on fifteen standard benchmark problem instances show that the proposed algorithm is comparable in terms of solution quality of other meta-heuristic algorithms. Manuscript profile -
Open Access Article
30 - The impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess return of investment funds and its role in Islamic financial marketing
Narges Salehi Azari Shadi Shahverdiani Gholamreza ZomorodianThe purpose of this research is to investigate the impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess returns of investment funds. In terms of method, the current research is a part of correlation research. In correlation research MoreThe purpose of this research is to investigate the impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess returns of investment funds. In terms of method, the current research is a part of correlation research. In correlation research, the researcher's effort is focused on discovering or determining the relationship between one or more variables. In fact, the purpose of this method is to study the limits of changes of one or more variables with the limits of changes of one or more variables, and from the point of view of the purpose of this research, it is an applied research, the results of which can be useful for shareholders, stock exchange officials, and researchers. It is useful and in terms of the type of post-event studies that examines hypotheses based on past financial data. The statistical population of this research includes all the companies admitted to the Tehran Stock Exchange during the period of 36 months in the period from April 2019 to March 2011, which number is 591 companies based on the Rahevard software. According to the conditions and application of the aforementioned restrictions, 150 companies were selected as a sample in the 36 months ending in March 1401. By observing the results of the stock portfolio selection models with single and combined measures, we find that in all three models, the amount of risk increases with the increase in return. This shows that investors, in order to obtain more return, They are forced to accept Manuscript profile -
Open Access Article
31 - Proposing a meta-heuristic method for solving network problems
A. M. Ahmadvand B. Farhad ZareBackground: Decision making is inseparable from management and it is considered as base for decision making. Decision making has an important role in the strategic level. Thus, strategies, models and variety methods are established to help managers which decision making MoreBackground: Decision making is inseparable from management and it is considered as base for decision making. Decision making has an important role in the strategic level. Thus, strategies, models and variety methods are established to help managers which decision making is one of them. Objective: There are different kinds of relations among the elements of decision making, particularly among criteria, for this purpose ANP method has proposed for involving all relations between elements of the problem. Method: ANP method is somehow sophisticated and time consuming that makes us to use softwares to solve the problems even a simple problem that often is concerned to strategist that needs a rapid reaction and less patience. The reason that strategies in most cases prefer AHP more than ANP in strategic situation is simplicity of the ANP posses in achieving to result but AHP doesn’t consider the dependency of the criteria's which results to wasting opportunities and capital because of choosing inappropriate strategy. Results: The meta-heuristic proposed method in this paper is named SIMANP that with it's simple mechanism, high accuracy, fast giving result, less time consuming and satiety to software solves the network problems accurate and easily. Conclusion: The SIMANP method will endow strategists and strategy managers who need accuracy, simple and fast giving result with the advantages of ANP Compared with AHP. Manuscript profile -
Open Access Article
32 - A Hybrid Meta-Heuristic Approach for Design and Solving a Location Routing Problem Considering the Time Window
Mohammad Amin Rahmani Ahamd Mirzaei Milad Hamzehzadeh Aghbelagh -
Open Access Article
33 - A Review of Feature Selection Method Based on Optimization Algorithms
Zohre Sadeghian Ebrahim Akbari Hossein Nematzadeh Homayun Motameni -
Open Access Article
34 - OPTIMIZING U-SHAPED MIXED ASSEMBLY LINES WITH A META- HEURISTIC GRASSHOPPER OPTIMIZATION ALGORITHM
Neda Mozaffari Hasan Mehrmanesh Mahmoud MohammadiFailure to achieve a balanced production system means not fully utilizing the capabilities of the production system, and because of the high cost of production systems, balancing these systems is one of the most important concerns of production managers. Is. For this re MoreFailure to achieve a balanced production system means not fully utilizing the capabilities of the production system, and because of the high cost of production systems, balancing these systems is one of the most important concerns of production managers. Is. For this reason, this study aimed to balance the complex assembly lines in order to reduce the cost of manpower and reduce the number of workstations. There are two general approaches to problem solving, To evaluate the problem under different conditions two problems of medium and large size are solved. First, an intermediate problem is solved by the exact method through the Gaussian software (GAMS) and the Salon Baron (BARON). Then again the intermediate problem is solved with the grasshopper meta-algorithm and their results are compared with the precise method and by this the accuracy and accuracy of the meta-metric method is measured so that it can be used to solve the large size problem. Finally, the values equal to the Grasshopper Algorithm Target Function and the Gaussian Target Function software show that the algorithm performs well, resulting in a large problem solved by the Grasshopper Metabolic Algorithm, resulting in cost savings and reduced workstations. Manuscript profile -
Open Access Article
35 - Designing a closed-loop supply chain mathematical model with an emphasis on empowering environmental capabilities and increasing profitability (military products case study)
abolfazl sadeghi Keyvan Sahgholian Akbar AlemtabrizThe main solution for companies to simultaneously achieve economic and environmental goals is to implement a closed loop supply chain. The main goal of this research is to design a mathematical model to empower the environmental capabilities and profitability of the clo MoreThe main solution for companies to simultaneously achieve economic and environmental goals is to implement a closed loop supply chain. The main goal of this research is to design a mathematical model to empower the environmental capabilities and profitability of the closed loop supply chain in military industries. The presented model is a 4-objective model, the first objective of which is to minimize emissions, the second objective is to minimize environmental waste, the third objective is to minimize cost, and the fourth objective is to minimize the risk of raw material supply. After designing the model, validation of the model has been done by solving it in small dimensions and then using four algorithms NSGAII, MOPSO, MOACO, MOSA to solve the model in medium and large dimensions and its results have been compared. Based on the results, the parameters of the model have been adjusted and the response of the model to different parameters has been investigated. The results show that simultaneous consideration of environmental and economic dimensions in the parameters leads to the improvement of the performance of the closed loop supply chain in terms of empowering the environmental capabilities and profitability. Manuscript profile -
Open Access Article
36 - Designing and explaining the pricing model in the four-level closed loop supply chain considering the uncertainty in the paper industry
Mahdi Alizadeh Beromi Mohammad Ali Afshar Kazemi Mohammadali Keramati abbas Toloie ashlaghiRecently, the supply chain of perishable goods, have been considered due to their impact on human life. On the other hand, in the packaging industry, considering paper as a primary and perishable material due to the nature of water absorption, severe rotting in front of MoreRecently, the supply chain of perishable goods, have been considered due to their impact on human life. On the other hand, in the packaging industry, considering paper as a primary and perishable material due to the nature of water absorption, severe rotting in front of sunlight, flammability and turning to ash and finally affecting the final quality of the product produced from this issue. It is not excluded, it has attracted more attention. The high level of speed of changes and ambiguity in decisions has made it impossible to predict the future conditions of supply chains. Therefore, the design and use of a mathematical model for the design of the closed-loop supply chain network, taking into account the optimal pricing of products, the return rate and demand, along with taking into account the wastage of materials in the system, is strongly needed. At first, the supply chain of the paper-cardboard industry was designed and modeled with mixed integer programming, then due to the high volume of calculations and data of the problem, we can't receive exact solution approaches, the innovative approach of searching for harmony was used for the solution. . The problem is a single-objective model that minimizes system costs by considering environmental considerations. The present research shows that the price increase has a positive effect on the product return rate and reducing the level of product corruption. Finally, to validate the model, the numerical solution of a closed loop network has been done in this industry. Manuscript profile -
Open Access Article
37 - Airlines Scheduling under Consideration, Operational constraints
Shokoh Kheradmand Mohamad Mohamadi Bahman NaderiFrom the past to the present due to the high costs of the aviation industry and planes, planning fir this particular industry has been furnished with a great deal of significance and attention.one of the issues concerning aviation industry, is navigation and the number MoreFrom the past to the present due to the high costs of the aviation industry and planes, planning fir this particular industry has been furnished with a great deal of significance and attention.one of the issues concerning aviation industry, is navigation and the number of planes required in each flight schedule. These issues include a significant part of the aviation industry costs. On the other hand, based on a series of restrictions and rules made by Airline companies in the flight schedule for each plane, obtaining an efficient flight schedule for determining the number of required planes and minimizing the costs related to planes and decreasing costs arising from lost sales is of great importance. On the other hand , given NP-hard state of this issue , exact solution models in large sizes is not possible, therefore with the help of Meta-heuristics such as genetic and simulation annealing ,we have dealt with exact solution models in large sizes and have compared the obtained results and reached a total overall. Manuscript profile -
Open Access Article
38 - Improvement of Imperialist Colony Algorithm by Employment of Imperialist Learning Operator and Implementing in Travel Salesman Problem
Hassan Haleh Daniyal Esmaeli Ali AbadiThis study tries to enhance imperialist colony algorithm (ICA) in the context of travel salesman problem (TSP). By adding new learning operator, imperialist learns form colonies that have suitable cost in which manner that improves solution of problems. We believe that MoreThis study tries to enhance imperialist colony algorithm (ICA) in the context of travel salesman problem (TSP). By adding new learning operator, imperialist learns form colonies that have suitable cost in which manner that improves solution of problems. We believe that controlled learning improvement is better than uncontrolled one. The efficiency of new operator represented with variety of instances from TSPLIB. We evaluate the approach on standard TSP test problems and show that it performs better, with respect to solution quality and computation time than ICA without new learning operator. Manuscript profile -
Open Access Article
39 - 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
40 - Optimization of Multi-period Three-echelon Citrus Supply Chain Problem
Navid Sahebjamnia Fariba Goodarzian Mostafa Hajiaghaei-Keshteli -
Open Access Article
41 - Participative Biogeography-Based Optimization
Abbas Salehi Behrooz Masoumi -
Open Access Article
42 - 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
43 - An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem
Amir Hossein Hosseinian Vahid Baradaran -
Open Access Article
44 - Solving Bi-objective Model of Hotel Revenue Management Considering Customer Choice Behavior Using Meta-heuristic Algorithms
Surur Yaghobi Harzandi Amir Abbas Najafi -
Open Access Article
45 - Developing a Fuzzy Green Supply Chain Management Problem Considering Location Allocation Routing Problem: Hybrid Meta-Heuristic Approach
Behzad Aghaei Fishani Ali Mahmoodirad Sadegh Niroomand Mohammad Fallah -
Open Access Article
46 - 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
47 - Hybrid Meta-heuristic Algorithm for Task Assignment Problem
Mohammad Jafar Tarokh Mehdi Yazdani Mani Sharifi Mohammad Navid Mokhtarian -
Open Access Article
48 - A Comparison of NSGA II and MOSA for Solving Multi-depots Time-dependent Vehicle Routing Problem with Heterogeneous Fleet
Behrouz Afshar-nadjafi Arian Razmi-farooji -
Open Access Article
49 - A Discrete Hybrid Teaching-Learning-Based Optimization algorithm for optimization of space trusses
Siamak Talatahari Vahid Goodarzimehr -
Open Access Article
50 - A Comparative Study of Meta-heuristic Algorithms for dynamic vehicle routing problem in order to provide efficiency of transportation systems
Nazila Mosayebzadeh Farzin Modarres khiyabaniVehicle Routing Problem (VRP) wasone of the mostpopularoptimization problems that hadmany usages for productivity andefficiency of transportation systems in recent decades.The VehicleRouting Problem with Simultaneous pick-up and deliveries (VRP/SPD),which considers simu MoreVehicle Routing Problem (VRP) wasone of the mostpopularoptimization problems that hadmany usages for productivity andefficiency of transportation systems in recent decades.The VehicleRouting Problem with Simultaneous pick-up and deliveries (VRP/SPD),which considers simultaneous distribution and collection of goodsfrom/to customers (VRP/SDP/SDC) was a variant of the classical vehiclerouting problem where customers require simultaneous pick-up anddelivery at their locations to be completed within a specified time.Applications of the SPD and its related variants are commonly comeacross in every day transportation and optimizing logistic planning. Thispaper had used Meta-heuristic to this end. The proposed method wasapplied for solving capacitated vehicle routing problem (CVRP) toimprove the distribution efficiency and productivity with an objective ofminimizing the total distance covered in each route, while consideringthe capacity of different routes. This problemwas essentially an NP-Hardin nature, so there was no known optimal solution method withpolynomial time. To solve this NP-hard VRP a hybrid genetic basedalgorithm was developed. The proposed geneticalgorithm was tested onsome standardproblem with respect to computational efficiency andsolution quality. The presented method was implemented and itsperformance was further investigated by comparing it against existingheuristics for the same problem. Theresults showed that the success ofthe proposed approach in handling the difficult problem constraints anddevising simple and robust solution mechanisms that can be integratedwith routing optimization tools and used in real world applications. Manuscript profile -
Open Access Article
51 - Routing in a Wireless Multilayer Physical Network by Balanced Utilization Approach and Minimum Energy Using a Firefly Optimization Algorithm
Abolghasem Nadali -
Open Access Article
52 - The Electricity Consumption Prediction using Hybrid Red Kite Optimization Algorithm with Multi-Layer Perceptron Neural Network
Jalal Raeisi-Gahruei Zahra BeheshtiSince the electricity consumption’s prediction is one of the most important aspects of energy manage­ment in each country, various methods based on artificial intelligence have been proposed to manage it. One of these methods is Artificial Neural Networks (ANN MoreSince the electricity consumption’s prediction is one of the most important aspects of energy manage­ment in each country, various methods based on artificial intelligence have been proposed to manage it. One of these methods is Artificial Neural Networks (ANN). To improve the performance of ANNs, an efficient algorithm is necessary to train it. Back Propagation (BP) algorithm is the most common algorithm employed in training ANNs, which is based on gradient descent. Since BP may fall in local optima, it cannot provide a good solution in some problems. To overcome this shortcoming, optimiz­ation algorithms like meta-heuristic algorithms can be applied to train ANNs. In this study, a new meta-heuristic algorithm called Red Kite Optimization Algorithm (ROA) is introduced, which is inspired by the social life of red kites in nature. The ROA has several advantages such as simplicity in structure and implementation, having few parameters and good convergence rate. The perfprmance of ROA is compared with some recent metaheuristic algorithms on benchmark functions of CEC2018. Also, it is employed to train Multi-Layer Perceptron (MLP) for the electricity consumption prediction at peak load times in Iran. The results show the good performance of proposed algorithm compared with competitor algorithms in terms of solution accuracy and convergence speed. Manuscript profile -
Open Access Article
53 - Investigation of seismic Fragility and collapse capacity of RC Moment Frames Considering the increase of stiffness of the column relative to the beam under far and near field earthquakes
siamak saboonchi ashkan khodabandehlouIn the present research, the seismic fragility and collapse capacity of concrete moment frames have been investigated by considering different ratios for the weak beam-strong column rule in the optimization process in the performance-based design framework. In order to MoreIn the present research, the seismic fragility and collapse capacity of concrete moment frames have been investigated by considering different ratios for the weak beam-strong column rule in the optimization process in the performance-based design framework. In order to implement performance-based optimization, the center of mass metaheuristic algorithm has been applied in this research. The philosophy of design approach based on performance and even traditional design methods allows the structure to suffer damage facing strong and relatively strong earthquakes. Therefore, in order to estimate the level of safety of the structure against earthquakes, it seems necessary to use quantitative indicators of seismic safety and the collapse capacity of the structure. In order to predict the collapse capacity of each optimal structure, using incremental dynamic analysis, the modified collapse safety margin ratio under far and near fault earthquakes has been calculated. Two examples, 3-span three and six floor frames have been studied in this research, which are designed in the performance-based optimization framework and considering the coefficients of 0.8, 1.2 and 1.6 to control the weak beam-strong column rule in the optimization process. The results indicate that increasing the rigidity of the column compared to the beam in this research actually affects the ductility of the structure, and by choosing structures with greater rigidity of the column compared to the beam, it leads to an increase in the collapse capacity and a decrease in the fragility of the structure. Manuscript profile -
Open Access Article
54 - The effect of far- and near-field earthquakes on the collapse capacity of performance based optimization of RC moment frames
siamak saboonchi ashkan khodabandehlouPerformance-based design is a new approach to topics of the seismic design of structures, which unlike the traditional methods of force-based design, is based on changing the location of the structure. The use of this approach in the process of structure design results MorePerformance-based design is a new approach to topics of the seismic design of structures, which unlike the traditional methods of force-based design, is based on changing the location of the structure. The use of this approach in the process of structure design results in the access to structures with proper performance and an acceptable level of reliability. The main goal of this contribution is to investigate the impact of near- and far- field earthquakes on the collapse capacity and fragility of performance based optimization of RC moment frames using the center of mass meta-heuristic algorithm. Push over analysis has been utilized in the optimization process to control the responses of the studied frames at functional levels and incremental dynamic analysis has been used to evaluate the fragility of the obtained optimal frames. According to the results for the collapse margin ratio and the adjusted collapse margin ratio for the 3-, 6-, and 12-story frames, it is indicated that the collapse margin ratio and therefore the seismic safety under far-field earthquakes are 7%, 16%, and 8% higher than those of the near-field earthquakes, respectively. In other words, the optimized frames in this study against near-field earthquakes have low seismic safety and more fragility than far-field earthquakes. Manuscript profile -
Open Access Article
55 - Fuzzy Portfolio Optimization Using Credibility Theory: Multi-Objective Evolutionary Optimization Algorithms
MariehAlsadat MirAboalhassani Farzad Movahedi Sobhani Emran Mohammadi -
Open Access Article
56 - A Review of Meta-heuristics Algorithms for Solving Fuzzy Location Routing Problems
Mehdi Fazli Somayyeh Faraji Amoogin -
Open Access Article
57 - بهینه ساز سنجاب پرنده (FSO): الگوریتم بهینه ساز نوین برمبنای هوش ازدحامی برای حل مسائل مهندسی
غلامرضا عزیزیان فرید میارنعیمی محسن راشکی ناصر شابختیدر پژوهش حاضر یک الگوریتم بهینه ساز نوین ارائه شده است. ایده اصلیِ این الگوریتم، از رفتار سنجاب های پرنده در یافتن غذا و نحوة تعامل آن ها با یکدیگر الهام گرفته شده است. این رفتار شامل پریدن از شاخه ای به شاخه دیگر برای نزدیک شدن به موقعیت غذا و سپس قدم زدن تصادفی برای د Moreدر پژوهش حاضر یک الگوریتم بهینه ساز نوین ارائه شده است. ایده اصلیِ این الگوریتم، از رفتار سنجاب های پرنده در یافتن غذا و نحوة تعامل آن ها با یکدیگر الهام گرفته شده است. این رفتار شامل پریدن از شاخه ای به شاخه دیگر برای نزدیک شدن به موقعیت غذا و سپس قدم زدن تصادفی برای دستیابی به موقعیتِ دقیق غذا می باشد. هم چنین سنجاب های پرنده توسط ایجاد صداهای کوچک و نازکی با یکدیگر ارتباط برقرار کرده و از محیط تقریبیِ غذاهایی هم چون بلوط و غیره، یکدیگر را آگاه می سازند. برای شبیه سازی دو رفتارِ مذکور نیز، به ترتیب از دو تئوری اساسی در حرکت ذرات، شامل پرواز لِوی و قدم زدنِ تصادفی استفاده شده است. نام این الگوریتم FSO می باشد. به علاوه، از دوازده تابع تست الگوریتم برای بررسی کارآیی این الگوریتم استفاده شده و نتایج بدست آمده با الگوریتم های MFO، PSO، GSA، BA، FPA، SMS و FA مقایسه شده است. نتایج حاکی از دقت الگوریتم ارائه شده در مقایسه با الگوریتم های قدرتمند مذکور بوده است. پنج مثال مهندسی نیمه واقعی کلاسیک و یک مثال در حلِ مسائلِ واقعی مربوط به سد بتنی وزنی نیز در این پژوهش ارائه شده است. نتایج بدست آمده نشان دادند که الگوریتم FSO را می توان در حل گستره وسیعی از مسائل مختلف و در محیط های متفاوت به کار برد. Manuscript profile -
Open Access Article
58 - Presenting a multi-objective mathematical model integrating production scheduling and maintenance considering the limited access to production resources in conditions of uncertainty and optimization with multi-objective genetic algorithm
محمد شریف زادگان محمدرضا حیدری کورش پوری عادل پورقادر چوبر میلاد ابوالقاسمیانIn production and industrial systems, the integrated planning of production and operations is very important. Responding quickly to the needs of customers, diversity, reliability and cost of equipment and machines, due to the extensive limitations in production resource MoreIn production and industrial systems, the integrated planning of production and operations is very important. Responding quickly to the needs of customers, diversity, reliability and cost of equipment and machines, due to the extensive limitations in production resources, competitiveness and gaining market share in conditions of uncertainty, there is a need to plan the units. be done in an integrated manner. In most of the production units, effective information is at an unfavorable level of coordination and exchange with other activities. The result of such activities is nothing but a waste of resources and the emergence of an insular culture in the organization. Therefore, in this research, a MIP mathematical model was modeled in line with the planning of production, maintenance in Maron Company. The objectives of the proposed model are to minimize production costs and maintenance costs with limited production resources. dependents such as maintenance) was used by the innovative method of genetics. The results of the modeling evaluation showed that the detailed and ultra-innovative solution provided has improved the company's production by more than 7%. Manuscript profile -
Open Access Article
59 - Communication-Aware Traffic Stream Optimization for Virtual Machine Placement in Cloud Datacenters with VL2 Topology
Sara Farzai Mirsaeid Hosseini Shirvani Mohsen Rabbani -
Open Access Article
60 - A Dual-Objective Nonlinear Model for Network Design with NSGA Algorithm
Bahar Khamfroush Mohamad Reza Akbari Jokar Keyhan Khamforoosh -
Open Access Article
61 - A Meta-heuristic Approach to CVRP Problem: Local Search Optimization Based on GA and Ant Colony
Arash Mazidi Mostafa Fakhrahmad Mohammadhadi Sadreddini -
Open Access Article
62 - Fuzzy modeling of allocation of financial resources of sustainable projects and Solving with GSSA algorithm
Mohsen Amini Khouzani Alireza Sadeghi Amir Daneshvar Adel Pourghader Chobar -
Open Access Article
63 - Improved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Raviteja Buddala Siba Sankar Mahapatra -
Open Access Article
64 - Effective heuristics and meta-heuristics for the quadratic assignment problem with tuned parameters and analytical comparisons
Mahdi Bashiri Hossein Karimi -
Open Access Article
65 - A modified elite ACO based avoiding premature convergence for travelling salesmen problem
M Yousefikhoshbakht E Mahmoodabadi M Sedighpour -
Open Access Article
66 - An integrated approach for scheduling flexible job-shop using teaching–learning-based optimization method
Raviteja Buddala Siba Sankar Mahapatra -
Open Access Article
67 - Presenting the Evolutionary Model of Short Selling Using Collective Intelligence and Ant Colony Algorithm
Sadegh Hojjati Arash Naderian Majid Ashrafi Jamadverdi Gorganli DojiThe purpose of this research is to present the evolutionary model of short selling using collective intelligence and an ant colony algorithm. In terms of method, this research is in the category of quantitative research, and the purpose of the study is practical. The st MoreThe purpose of this research is to present the evolutionary model of short selling using collective intelligence and an ant colony algorithm. In terms of method, this research is in the category of quantitative research, and the purpose of the study is practical. The statistical population includes all active companies admitted to the Tehran Stock Exchange. This research has been investigated between 2011 and 2019 for active companies admitted to the Tehran Stock Exchange. The method of data collection is library-type and uses foreign and domestic articles and financial data of companies admitted to the stock exchange, which has been compiled by referring to financial statements and explanatory notes using the new Rahvard Novin software. In the following, we have presented the short-selling model by using EViews 9 software and MATLAB, and then using MATLAB software and the ant colony algorithm, we have presented the evolutionary model of short selling. In the end, by comparing the step-by-step regression model and the borrowed sales model (ant colony algorithm), he presented a model that is more efficient than other models. The result of the research indicates that the short-selling model with the help of the ant colony algorithm has a higher efficiency. Manuscript profile -
Open Access Article
68 - Estimation of loan repayment loss in Sarmayeh Bank using weed optimization meta-heuristic algorithm
zahra Rahmani Mohammad Ebrahim Mohammadpoor Zarandi Mohammadali keramatiLiquidity management has been one of the biggest challenges facing the banking system in Iran in the acute inflation conditions in recent years. Facilities granted by banks, regardless of inflationary conditions, usually lead to hidden losses in repayment of loans, resu MoreLiquidity management has been one of the biggest challenges facing the banking system in Iran in the acute inflation conditions in recent years. Facilities granted by banks, regardless of inflationary conditions, usually lead to hidden losses in repayment of loans, resulting in reduced profitability and the risk of inability to meet obligations, resulting in the risk of bankruptcy. The present study aims to estimate the loan repayment loss in Sarmayeh Bank using the weed optimization meta-heuristic algorithm. In the present study, a model was designed to examine the loan repayment loss. Also, to compare the calculated results using the proposed heuristic formula and the income of the granted financial facilities in terms of loan repayment loss prediction, weed optimization meta-heuristic algorithm was used. The results showed that there is a negative correlation between loan repayment losses and the growth of Sarmayeh Bank profitability in high inflation conditions. Also, comparing the loan loss prediction between the calculated results using the proposed heuristic formula, the number predicted by the weed optimization algorithm and the income of the granted financial facilities showed that the loan repayment loss using the weed optimization meta-heuristic algorithm can be calculated. Manuscript profile -
Open Access Article
69 - The Effect of Demand-Response Program and Distributed Generation Resources on Optimal Establishment of Electric Vehicle Charging/Discharging Stations Using a Triple Optimization Algorithm
Monireh Ahmadi Seyed Hossein Hosseini Murteza Farsadi -
Open Access Article
70 - Presentation of intelligent Meta-heuristic Hybrid models (ANFIS -MGGP ) to predict stock returns with more accuracy and speed than other Meta-heuristic methods.
mahmood kohansal kafshgari Alireza Zarei reza behmaneshDiscussions about forecasting Stock returns in developed countries has long been regarded as one of the most interesting scientific topics.However,due to many problems,the correct prediction of stock returns has remained a matter of strengthTtherefore,the researcher see MoreDiscussions about forecasting Stock returns in developed countries has long been regarded as one of the most interesting scientific topics.However,due to many problems,the correct prediction of stock returns has remained a matter of strengthTtherefore,the researcher seeks to provide an accurate,practical and effective model for predicting stock returns for investors.The statistics sampel of research is consist of 138 active companies in Tehran Stock Exchange from 2008 to 2017 wich are selected by the systematic removal method . ANFIS,MGGP, regresion and neural network and different statistics tests are used for data analysis. For impelement of these techniques MATLAB and GenXproTools software are used respectively.The result of the study showed that in oreder to predict stock returns.the use of a meta –heuristic Hybrid models is more accurate and faster than other meta huristic models.Because ,first the most optimal input variables are selected through the ANFIS technique and then predicted using theMGG meta heuristic model.Therefore,due to the correct choice of input variables,predicting stock returns is both more accurate and faster.In addition ,the mathematical model is used to predict. Manuscript profile -
Open Access Article
71 - 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
72 - Portfolio optimization in capital market bubble space, application of bee colony algorithm
Iman Mohammadi Hamzeh Mohammadi Khashoei arezoo aghaei chadeganiThe existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other han MoreThe existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other hand,due to the goal of investors in achieving a high return portfolio with the least amount of risk,it is necessary to pay more attention to these markets In this study,in order to maximize returns and minimize investment risk,an attempt was made to create an optimal portfolio in conditions where the capital market has a price bubble.According to the purpose,the research is of applied type,and in terms of data,quantitative and post-event,and in terms of analysis,is descriptive-correlation.In order to identify bubble months in the period from2015to2019in Tehran Stock Exchange,sequence tests and skewness and kurtosis tests were used and after identifying bubble periods,artificial bee colony algorithm was used to optimize the portfolio.The results indicate the identification of 10 periods with a price bubble in the study period.Also,in portfolio optimization, selected stock portfolios are formed with maximum returns and minimum risk.This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions. Manuscript profile -
Open Access Article
73 - Smart operating system based on technical parameters optimized with firefly algorithm
Fatemeh Asiaei Taheri Gholamreza zomorodian Mirfeiz FallahshamsThe main goal of investors in the stock market is to get the highest return at the desired time, therefore introducing the most suitable method for conducting transactions is of special importance for investors. Successful trading in financial markets should be done clo MoreThe main goal of investors in the stock market is to get the highest return at the desired time, therefore introducing the most suitable method for conducting transactions is of special importance for investors. Successful trading in financial markets should be done close to key reversal points. In recent years, various systems have been developed to identify these return points. Technical analysis tries to identify the time to enter and exit trades.In this article, we are trying to select the one with a higher success rate by using the technical rules according to the previous researches, and by using soft calculations, the decision parameters in the technical rules are improved using the firefly algorithm.The results of this model are compared with the results of using the standard parameters of the indicators and the results of the purchase and maintenance strategy. In order to validate the introduced trading system, we compared it with the results of the optimized intelligent system based on optics and genetic algorithm. The results of the research show that by optimizing the parameters of technical analysis indicators, the investment efficiency can be increased compared to the usual methods in the stock market and previous researches. Manuscript profile -
Open Access Article
74 - Optimization of technical indicators’ parameters for intraday data using optics – inspired optimization (OIO): a case study of Tehran stock exchange
Mohammad Ali Rastegar Farah AshuriIn this paper a stock trading system based on the combination of six technical indicators is designed. The indicators are combined using an artificial neural network and their parameters are optimized using convex combination-based optics-inspired optimization (COIO) al MoreIn this paper a stock trading system based on the combination of six technical indicators is designed. The indicators are combined using an artificial neural network and their parameters are optimized using convex combination-based optics-inspired optimization (COIO) algorithm. In the proposed model the technical indicators’ optimized parameters are obtained using both COIO and genetic algorithms with the aim of maximization of modified Sharpe ratio. The presented paper uses stock intra-day prices as input data and considers the transaction costs. The designed strategy is compared against several other approaches including: using the indicators’ default parameters, buy and hold strategy and optimization using genetic algorithm, for both daily and intra-day prices and due to a greater modified Sharpe ratio for the proposed model, its superiority is shown in all cases. Moreover, in a comparison based on end- of- period returns, it is shown that without considering the transaction costs the results of the intra-day data beats the results of the daily data while no superiority is observed when considering the transaction costs. So reducing the transaction costs is recommended to motivate traders to trade on an intra-day basis. Manuscript profile -
Open Access Article
75 - Improving the Performance of Adaptive Neural Fuzzy Inference System (ANFIS) Using a New Meta-Heuristic Algorithm
Mehdi Khadem Abbas Toloie Eshlaghy Kiamars Fathi hafshejani -
Open Access Article
76 - A Multi-objective Leagile Demand-Driven Optimization Model incorporating a Reliable Omnichannel Retailer: A Case Study
Farnaz Javadi Gargari Zahra Saeidi-Mobarakeh Hossein Amoozad KhaliliThis research proposed a comprehensive model designed for the optimization of supply chain networks, particularly emphasizing leagile demand-driven systems within the context of omnichannel operations. The proposed model integrates various parameters such as total cost, MoreThis research proposed a comprehensive model designed for the optimization of supply chain networks, particularly emphasizing leagile demand-driven systems within the context of omnichannel operations. The proposed model integrates various parameters such as total cost, lead time, service level, and residual capacity, addressing the complex interdependencies among an omnichannel environment of retailers. To enhance the model's reliability, a hybrid meta-heuristic algorithm is employed, combining the strengths of MOEA/D-DE (Multi-Objective Evolutionary Algorithm with Differential Evolution), IBEA (Indicator-Based Evolutionary Algorithm), and NSGA-II (Non-dominated Sorting Genetic Algorithm II). The collaborative optimization approach ensures adaptability and efficiency in addressing diverse and intricate optimization challenges inherent in omnichannel networks. The numerical data from a case study on the supply of sanitary masks in Tabriz, Iran, during August 2021 is utilized to validate the model within the specific omnichannel context. The study includes a thorough sensitivity analysis, demonstrating the model's robustness against disturbances in the omnichannel network. The consistent performance of the odel across various disruption scenarios underscores its reliability and efficacy in ensuring the stability of supply chain operations within omni-channel frameworks. This observed resilience significantly enhances the overall robustness of the supply chain, especially when confronted with disruptive events. The model's ability to maintain stability under diverse conditions contributes to fortifying the supply chain against potential disruptions, thereby augmenting its adaptive capabilities in dynamic environments..Managerial and practical implications are discussed, emphasizing the significance of the proposed reliable omnichannel approach in leagile demand-driven systems. Manuscript profile