Improved Particle Swarm Optimization With Dynamically Changing Inertia Weight

摘要：

In order to improve the performance of particle swarm (PSO) algorithm which inertia weight was decreased linearly, a novel particle swarm optimization (NPSO) algorithm with dynamically changing inertia weight was presented. In each iteration process, the inertia weight of the improved algorithm was changed dynamically based on the current iteration and the best fitness. The new algorithm was tested with three benchmark functions. The test results indicated that the disadvantages of slow speed on convergence and easy to be trapped in local optimum of the linearly decreasing weight of the PSO could be overcome effectively.

关键词： Particle Swarm Optimization Dynamic inertia weight Convergence velocity Premature

作者: Dongyun Wang Ping Zeng Kai Wang Luowei Li

作者单位: Department of Electronic&Information, Zhongyuan Institute of Technology, Zhengzhou Henan 450007 China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Technology and Industrial Engineering(2010年信息技术与工业工程国际学术会议 ITIE 2010)

会议地点: 武汉

会议语种:英文

页码: 805-808

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