Mutative Scale Chaos Particle Swarm Optimization Algorithm

摘要：

This paper presents a new particle swarm optimization (PSO)algorithm,using the method of mutative scale chaos optimization algorithm.We call the new algorithm MSCPSO,and it can be used to solve the function optimization problem.Each time when the PSO finishes searching,we try to use the chaotic search operator to get a better solution near the current global optimal solution.As the PSO keeps running,the search vicinity will become smaller.The chaotic search operator,in the initial phase,plays the role of preventing a local optimum;while in the later phase,it plays the role of improving search accuracy.A set of benchmark functions is used to test MSCPSO,and the experiment results show that MSCPSO is good at solving function optimization problems including cheating functions and high-dimensional functions.

关键词： Particle swarm optimization Chaos Mutative Scale function optimization

作者: Hong-gang Wang Liang Ma Hui-zhen Zhang Gao-ya Li

作者单位: Business School,University of Shanghai for Science and Technology,200093

会议类型: 国际会议

会议名称: 2008 International Conference on System Management(2008年系统管理学术研讨会)(2008 CSM)

会议地点: 上海

会议语种:英文

页码: 71-77

在线出版日期: 2008-05-30（万方平台首次上网日期，不代表论文的发表时间）