A Share Historical and Global Best Particle Swarm Optimization Algorithm

摘要：

This article advances a share historical and global best particle swarm optimization algorithm (SGHPSO). In SGHPSO model, particles fully inherit the information of historical and global optimum particles in previous operation, which increases the search efficiency of particles. Ten typical nonlinear functions are given to test the efficiency of the improved algorithm. Simulation results clearly demonstrate superiority of the improved algorithm.

关键词： Historical global inherit PSO

作者: Lian Zhigang Hu Keyi Jiang Zhibin Zheng Dongbiao

作者单位: Electronic and Information School Shanghai DianJi University Shanghai, China Jiangnan Shipyard(Group),Co.,Ltd, Shanghai School of Mechanical Engineering Shanghai Jiao Tong University Shanghai, China

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 526-530

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）