Abstract—The Particle Swarm Optimization (PSO) algorithm, as one of the latest algorithms inspired from the nature, was introduced in the mid 1990s and since then, it has been utilized as an optimization tool in various applications, ranging from biological and medical applications to computer graphics and music composition. In this paper, following a brief introduction to the PSO algorithm, the chronology of its evolution is presented and all major PSO-based methods are comprehensively surveyed. Next, these methods are studied separately and their important factors and parameters are summarized in a comparative table. In addition, a new taxonomy of PSO-based methods is presented. It is the purpose of this paper is to present an overview of previous and present conditions of the PSO algorithm as well as its opportunities and challenges. Accordingly, the history, various methods, and taxonomy of this algorithm are discussed and its different applications together with an analysis of these applications are evaluated.
Index Terms—Heuristic Optimization, Particles Swarm Optimization (PSO), Taxonomy, Applications.
D. Sedighizadeh is with the Faculty of Engineering, Tarbiat Modares University, Tehran, 14115-143, Iran (phone: +98-21-82883145; fax: +98-21-82884180; e-mail: email@example.com).
＊Corresponding aurhor: E. Masehian is an assistance professor in the faculty of engineering, Tarbiat Modares University, Tehran, Iran（e-mail: Masehian@modares.ac.ir.）
Cite: Davoud Sedighizadeh and Ellips Masehian, "Particle Swarm Optimization Methods, Taxonomy and Applications," International Journal of Computer Theory and Engineering vol. 1, no. 5, pp. 486-502, 2009.