Kharazmi University International Journal of Supply and Operations Management 2383-1359 2 1 2015 05 01 An Expert System for Intelligent Selection of Proper Particle Swarm Optimization Variants 569 594 2351 10.22034/2015.1.03 EN Ellips Masehian Tarbiat Modares University, Teahran, Iran Vahid Eghbal Akhlaghi Middle East Technical University, Ankara, Turkey Hossein Akbaripour Tarbiat Modares University, Teahran, Iran Davoud Sedighizadeh Islamic Azad University, Saveh branch, saveh, Iran Journal Article 2015 04 16 Regarding the large number of developed Particle Swarm Optimization (PSO) algorithms and the various applications for which PSO has been used, selecting the most suitable variant of PSO for solving a particular optimization problem is a challenge for most researchers. In this paper, using a comprehensive survey and taxonomy on different types of PSO, an Expert System (ES) is designed to identify the most proper PSO for solving different optimization problems. Algorithms are classified according to aspects like particle, variable, process, and swarm. After integrating different acquirable information and forming the knowledge base of the ES consisting 100 rules, the system is able to logically evaluate all the algorithms and report the most appropriate PSO-based approach based on interactions with users, referral to knowledge base and necessary inferences via user interface. In order to examine the validity and efficiency of the system, a comparison is made between the system outputs against the algorithms proposed by newly published articles. The result of this comparison showed that the proposed ES can be considered as a proper tool for finding an appropriate PSO variant that matches the application under consideration. http://www.ijsom.com/article_2351_0abdc563a06105aee3c6136871c9f4d1.pdf