List of Articles الگوریتم‌های فراابتکاری

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  1 - Efficiency analysis of the meta-heuristic algorithms in portfolio optimization
  Sina Shirtavani Mehdi Homayonfar Keyhan Azadi amir daneshvar
  The 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 More

  The 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
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  2 - The indifference points in multi-criteria decision problems (case stady Evalution Supplyers in Zanjan Province Water and Wastewater Company)
  Reza Radfar ARSHAD FARAHMANDIAN Mohammad Ali Afshar Kazemi
  Decisions on the process of assessment and selection of suppliers should be made by examining all possible options, otherwise the organization will encounter many problems during the implementation and implementation phases.The purpose of the present study was to determ More

  Decisions on the process of assessment and selection of suppliers should be made by examining all possible options, otherwise the organization will encounter many problems during the implementation and implementation phases.The purpose of the present study was to determine the indifference points of assessors of the water and wastewater company in Zanjan province.The method of this study was descriptive. The data of this study is related to supplier assessment of one of the projects of the city water and wastewater company Zanjan province.The data was collected based on the views of 10 experts with at least a bachelor's degree and at least 5 years of work experience in the company based on the "supplier assessment form".The data has been analyzed using the 2014 version of MATLAB software.A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method.TOPSIS-GA = 2 and TOPSIS-PSO = 3 and AHP-GA = 2 and AHP-PSO = 3. A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method. Manuscript profile
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  3 - Comparing and Ranking of Meta-Heuristic Algorithms Using Group Decision Making Methods
  Hojatollah Rajabi Moshtaghi Abbas Toloie Eshlaghy Mohammad Reza Motadel
  10.30495/imj.2022.688625
  In 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 More

  In 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
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  4 - Power and weight optimization of spur gears using metaheuristics and finite element method
  Mohammad Sadeghi Ali Sadollah
  Gearing is one of the most efficient methods of transmitting power from a source to its application with or without change of speed or direction. In this paper, a spur gear model is optimized aiming to maximize its transmission power and minimize its weight. Several des More

  Gearing is one of the most efficient methods of transmitting power from a source to its application with or without change of speed or direction. In this paper, a spur gear model is optimized aiming to maximize its transmission power and minimize its weight. Several design variables named as transmitted power, number of pinion teeth, modules, and thickness of gears have been considered during optimization process. For the sake of optimization, two developed metaheuristics named as water cycle and neural net-work algorithms have been examined using MATLAB programming language platform. Besides, obtained optimization results have been validated and analyzed using well-known commercial computer aided engineering software ANSYS. Based on the ob-tained optimization results, optimum design has been found using optimizers and in terms of engineering analysis good agreement has been observed between the applied finite element approach. Manuscript profile
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  5 - Airlines Scheduling under Consideration, Operational constraints
  Shokoh Kheradmand Mohamad Mohamadi Bahman Naderi
  From 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 More

  From 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
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  6 - The Electricity Consumption Prediction using Hybrid Red Kite Optimization Algorithm with Multi-Layer Perceptron Neural Network
  Jalal Raeisi-Gahruei Zahra Beheshti
  Since 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 More

  Since 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
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  7 - Smart operating system based on technical parameters optimized with firefly algorithm
  Fatemeh Asiaei Taheri Gholamreza zomorodian Mirfeiz Fallahshams
  The 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 More

  The 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
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  8 - Meta-heuristic Algorithms for the Tower Crane Planning on the Site
  Roya Amiri Javad Majrouhi Sardroud Vahid Momenaei Kermani
  Research projects show that the desire for intelligent approaches to decision-making at various stages of the construction industry is increasing. Site layout planning is one of the important decision-making processes in the early stages of construction projects, where More

  Research projects show that the desire for intelligent approaches to decision-making at various stages of the construction industry is increasing. Site layout planning is one of the important decision-making processes in the early stages of construction projects, where the location of facilities must be determined within the site. Tower crane is considered as one of the vital and expensive facilities in construction sites. Proper locating of tower crane has a significant impact on the quality, productivity, safety, cost and time of the project. In choosing the location of the tower crane, there are several criteria, including the largest lifting radius and capacity of the tower crane, the type of soil on site, the soil-bearing capacity and the material supply points. Therefore, due to the influence of many factors, tower crane planning is a complex NP-hard optimization problem, which cannot be solved through exact mathematical algorithms as the number of parameters and variables increases. Therefore, it is necessary to define the problem as an optimization problem and integrate it with mathematical modeling to reach the optimal solution. Solving such problems is usually done through metaheuristic algorithms, which belong to the category of approximate algorithms. This study provides a comprehensive review on tower crane planning problem on construction sites using mathematical modeling and metaheuristic algorithms. Based on the findings of this study, research gaps are identified in this field. Therefore, suggestions for future works have been presented in order to solve the shortcomings, which can be the subject of various research articles. Manuscript profile