Particle Swarm Optimization based on an Improved Diversity Mechanism

摘要：

Particle swarm optimization (PSO) algorithm has shown fast and good search abilities in many unimoal and simple multimodal problems. However, PSO as well as other evolutionary algorithms (EAs) also suffers from the problem of premature convergence in solving some complex multimodal problems. The main reason is that the diversity of swarm decreases very quickly. In this paper, we propose a new PSO variant (DPSO) based on an improved diversity mechanism. Experimental verifications on 13 famous benchmark functions show that the proposed approach achieves better results than standard PSO on the majority of test problems.

关键词： particle swarm optimization (PSO) diversity global optimization

作者: Liyan Ma Ziping Guo Huifang Cheng

作者单位: School of Information & ElectronicEngineering Hebei University ofEngineering Handan 056038, China Department of InformationHanDan Design and ResearchInstitute of Conservancy andHydropower School of Information & Electronic Engineering Hebei University of Engineering Handan 056038, China

会议类型: 国际会议

会议名称: 2010 2nd IEEE International Conference on Information Management and Engineering(2010年IEEE第二届信息管理与工程国际会议 IEEE ICIME 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-04-16（万方平台首次上网日期，不代表论文的发表时间）