The Random Factor in Particle Swarm Optimiazation

摘要：

The paper introduces the random factor in Particle Swarm Optimization. Comparing with inertia weight, the particles velocity is determined by previous velocity, own experience, public knowledge and random behavior. The random operator is similar with the mutation operator in the Genetic Algorithms. Simulation results show that the method introducing the random factor is better than inertia weight and constriction factor.

关键词： Particle Swarm Optimization random operator inertia weight constriction factor

作者: Xiaohong Qiu Jun Liu Xuemei Ren

作者单位: School of Software Jiangxi Agricultural University Nanchang,330045,China Department of Automatic Control Beijing Institute of Technology Beijing,100081,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 787-791

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）