Particle Swarm Optimization with Adaptive Mutation

摘要：

Particle swarm optimization (PSO) has shown its good performance in many optimization problems. However, PSO could often easily fall into local minima because the particles could quickly converge to a position by the attraction of the best particles. Under this circumstance, all the particles could hardly be improved. This paper presents a hybrid PSO (AMPSO) to solve this problem by applying a novel adaptive mutation operator. Experimental results on 8 well-known benchmark functions show that the AMPSO achieves better results than the standard PSO, PSO with Gaussian mutation and PSO with Cauchy mutation on most test cases.

关键词： Particle swarm optimization (PSO) mutation function optimization

作者: Jun Tang Xiaojuan Zhao

作者单位: Department of Information Engineering Hunan Urban Construction College Xiangtan, China

会议类型: 国际会议

会议名称: 2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)

会议地点: 太原

会议语种:英文

页码: 893-896

在线出版日期: 2009-07-10（万方平台首次上网日期，不代表论文的发表时间）