A Modified Quantum-behaved Particle Swarm Optimization with Gaussian Disturbance on Mean Best Position

摘要：

Based on the previously introduced Quantum-behaved Particle Swarm Optimization (QPSO), a revised QPSO with Gaussian disturbance on the mean best position of the swarm is proposed. The reason for the introduction of this novel method is that the disturbance can effectively prevent the stagnation of the particles and therefore make them escape the local optima and sub-optima more easily. Before proposing the Revised QPSO (RQPSO), we introduce the origin and the development of the original PSO and QPSO. To evaluate the performance of the new method, the Revised QPSO, along with QPSO and Standard PSO, is tested on several well-known benchmark functions. The experimental results show that the Revised QPSO has better performance than QPSO and Standard PSO generally.

作者: Xiaogen Wang Jun Sun Wenbo Xu

作者单位: School of Education Southern Yangtze University Wuxi, Jiangsu 214122 School of Information Technology Southern Yangtze University Wuxi, Jiangsu 214122

会议类型: 国际会议

会议名称: Fourth International Conference on Impulsive and Hybrid Dynamical Systems(ICIHDS 2007)(第四届国际脉冲和混合动力系统学术会议)

会议地点: 南宁

会议语种:英文

在线出版日期: 2007-07-20（万方平台首次上网日期，不代表论文的发表时间）