An Improve PSO Based Hybrid Algorithms

摘要：

This paper used Particle swarm optimization (PSO) algorithms and its hybrid algorithms such as PSOPC and UPSO for solving optimization problems. Particle swarm optimization with passive congregation (PSOPC) and the unified PSO algorithm is called UPSO use to improve the performance and convergence of standard PSO. Passive congregation is an important biological force preserving swarm integrity and presents a unified PSO to improve convergence. A hybrid PSO algorithm such as UPSO and PSOPC are tested with 6 benchmark functions and simulation result compared whit standard genetic algorithm and standard Particle swarm optimization algorithm, respectively. Experiment result indicates that the PSOPC and UPSO improve the search convergence and performance on the benchmark function significantly.

作者: H.Babaee A.Khosravi

作者单位: Faculty of Electrical and Computer Engineering Noushirvani University of Technology, Babol, 47135-484, Iran

会议类型: 国际会议

会议名称: International Conference on Management and Service Science(2011年第五届管理与服务科学国际会议 MASS 2011)

会议地点: 武汉

会议语种:英文

页码: 1-5

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）