University of Tabriz Applied Theories of Economics 2423-6586 8 4 2022 02 20 Optimization of Stock Portfolio Selection in Iran Capital Market Using Meta-heuristic Algorithms Optimization of Stock Portfolio Selection in Iran Capital Market Using Meta-heuristic Algorithms 253 284 14359 10.22034/ecoj.2022.47049.2913 FA Sobhan Mostafayi Darmian Department of Industrial Engineering, Kurdestan University, Kurdestan, Iran Meysam Doaei Department of Finance, Esfarayen Branch, Islamic Azad University, Esfarayen, Iran Journal Article 2021 07 18 The purpose of this study is to optimize the portfolio in companies listed on the Iran capital market (Tehran Stock Exchange and Iran Farabours) as a multi-objective optimization problem. The first objective function includes risk minimization and the second objective function includes return maximization. The limitations of the model include the limitation of selecting companies individually as well as the limitation of budget. In order to solve the problem, two genetic metaheuristic algorithms and a gray wolf have been developed, which are analyzed using numerical examples taken from 491 companies listed on the Tehran Stock Exchange and the Iran Farabours market from April 26, 2016 to December 21, 2022 were subjected to numerical analysis.<br />According to the numerical results, it can be seen that the gray wolf algorithm has a higher efficiency than the genetic algorithm in all examples. It is noteworthy, however, that in none of the numerical examples did the percentage of unwarranted responses in the algorithm improvement procedure exceed 10.2%. Also, the percentage improvement of the gray wolf algorithm compared to the genetic algorithm is reported to be between 3 and 11%. The purpose of this study is to optimize the portfolio in companies listed on the Iran capital market (Tehran Stock Exchange and Iran Farabours) as a multi-objective optimization problem. The first objective function includes risk minimization and the second objective function includes return maximization. The limitations of the model include the limitation of selecting companies individually as well as the limitation of budget. In order to solve the problem, two genetic metaheuristic algorithms and a gray wolf have been developed, which are analyzed using numerical examples taken from 491 companies listed on the Tehran Stock Exchange and the Iran Farabours market from April 26, 2016 to December 21, 2022 were subjected to numerical analysis.<br />According to the numerical results, it can be seen that the gray wolf algorithm has a higher efficiency than the genetic algorithm in all examples. It is noteworthy, however, that in none of the numerical examples did the percentage of unwarranted responses in the algorithm improvement procedure exceed 10.2%. Also, the percentage improvement of the gray wolf algorithm compared to the genetic algorithm is reported to be between 3 and 11%. https://ecoj.tabrizu.ac.ir/article_14359_a39fa5b5b2c00da9fe4dda1753041f19.pdf