A Novel Particle Swarm Optimization Algorithm

摘要：

A novel particle swarm optimization algorithm based on the Gaussian probability distribution is proposed in this paper. The standard Particle Swarm optimization (PSO) algorithm has some parameters that need to be specified before using the algorithm, e.g., the accelerating constants c1 and c2, the inertia weight w, the maximum velocity Vmax, and the number of particles of the swarm. The purpose of this work is the development of an algorithm based on the Gaussian distribution, which improves the convergence ability of PSO without the necessity of tuning these parameters. The only parameter to be specified by the user is the number of particles. The Gaussian PSO algorithm was tested on a suite of well-known benchmark functions and the results were compared with the results of the standard PSO algorithm.

关键词： Particle Swarm Optimization Gaussian distribution nonlinear optimization

作者: Xiaogang Wang Yan Bai Yue Li

作者单位: Wuhan University of Science and Engineering Wuhan City, Hubei Province, China 430073

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 408-411

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）