Mutated Fast Convergent Particle Swarm Optimization and Convergence Analysis

摘要：

The particle swarm optimization(PSO)is an algorithm to find out optimal solution irr search space by interactions of individuals among particle population.Every though the hierarchical PSO(HPSO)algorithm. which is consisted of fast position convergence particle swarm optimization(fPSO)layer acrd mutation layer,has been shown to perform well,but the analysis of convergent condition of,fPSO has not been given by the authors.In this paper, the corrvergerrt sufficient condition of fPSO in HPSO algorithm is derived mathematically,and a HPSO like mutated fPSO(mfPSO)is constructed too.Results of experiments show that the introduced mfPSO performed superiority to HPSO orr benchmarks.

作者: CAI Biao Li Zhishu Fu Die Hu Jian Ou Peng Li Qing

作者单位: School of Computer Science,Sichuan University,Chengdu,Sichuan,P.R.China,610065 Network Management Center Sichuan University of Art and Science,Dazhou,Sichuan,P.R.China,635000

会议类型: 国际会议

会议名称: 第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

会议地点: 武汉

会议语种:英文

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）