Using Accelerator Feedback to Improve Performance of Integral-Controller Particle Swarm Optimization

摘要：

Integral-controller particle swarm optimization (ICPSO), influenced by inertia weight w and coefficient ψ is a new swarm technology by adding accelerator information. Based on stability analysis, the convergence conditions imply the negative selection principles of inertia weight w, and the relationship between w and ψ. To improve the computational efficiency, an adaptive strategy for tuning the parameters of ICPSO is described using a new statistical variable reflecting computational efficiency index-average accelerator information. The optimization computing of some examples is made to show that the ICPSO has better global search capacity and rapid convergence speed.

关键词： Particle swarm optimization Average Accelerator Information Integral-controller

作者: Zhihua Cui Jianchao Zeng Guoji Sun

作者单位: State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xian, 710049 Division of System Simulation and Computer Application, Taiyuan University of Science and Technology State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xian, 710049

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 665-668

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）