Optimal choice of parameters for particle swarm optimization

• Published in: Journal of Zhejiang University. A. Science Vol. 6; no. 6; pp. 528 - 534
• Main Author: 张丽平 俞欢军 胡上序
• Format: Journal Article
• Language: English
• Published: Department of Chemical Engineering, Zhejiang University, Hangzhou 310027, China 01.06.2005
• Subjects: 压缩要素; 参数选择; 基准函数; 最优化组合; 粒子集合; Particle swarm optimization (PSO); Constriction factor method (CFM); Parameter selection
• ISSN: 1673-565X; 1862-1775
• DOI: 10.1631/jzus.2005.A0528

The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the performance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and improper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper.