Local and Global Search Based PSO Algorithm

摘要：

　　In this paper, a new algorithm for particle swarm optimisation (PSO) is proposed.In this algorithm, the particles are divided into two groups.The two groups have different focuses when all the particles are searching the problem space.The first group of particles will search the area around the best experience of their neighbours.The particles in the second group are influenced by the best experience of their neighbors and the individual best experience, which is the same as the standard PSO.Simulation results and comparisons with the standard PSO 2007 demonstrate that the proposed algorithm effectively enhances searching efficiency and improves the quality of searching.

关键词： Local search global search particle swarm optimisation

作者: Yanxia Sun Zenghui Wang Barend Jacobus van Wyk

作者单位: Department of Electrical Engineering, Tshwane University of Technology,Pretoria 0001, South Africa Department of Electrical and Mining Engineering, University of South Africa,Florida 1710, South Afri

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 129-136

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）