A Switching Particle Swarm Optimization for Multimodal Optimization Problem

摘要：

　　Particle swarm optimization(PSO)has a variety of applications on optimization problems,and it has been proved better convergence performance than former evolutionary algorithms(as GA),but the standard PSO algorithm is sensitive to fall into local optima,especially for multimodal optimization problem.To deal with this case,this paper proposes an switching PSO algorithm with a novel velocity update mechanism and switching mode based on entropy of swarm and the global optima,according to which the proposed PSO changes velocity and particle update formula.Some benchmark tests were performed,and numerical results show advantages in comparison with performance of standard PSO.

关键词： PSO Switching PSO Switching mode Entropy

作者: Dongmei WU

作者单位: School of Automation,Nanjing University of Posts and Telecommunications,Nanjing 210023

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 7585-7588

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）