Study on Multiple Attractors Particle Swarm Optimization and Its Application

摘要：

To overcome the disadvantages of precocity and stagnation phenomenon of the standard particle swarm optimization algorithm,this paper proposes an improved particle swarm algorithm.Firstly,in the process of selecting an initial solution, the improved greedy strategy is used to directly obtain a group of initial solutions with high performance to improve the search efficiency of the algorithm.Secondly,by introducing sub-optimal attractor.the particles in the search process can make full use of colonial information to improve their own performances as to effectively inhibit stagnation in the process of convergence,and improve the searching capability of the algorithm proposed in the article.In order to verify the effectiveness and feasibility of the proposed algorithm,many cases in two unrestrained optimization and the standard library TSPLIB have been tested. Compared with other algorithms, this improved particle swarm optimization is very effective.

关键词： Particle Swarm Multiple Attractors, optimization algorithm Traveling Salesman Problem

作者: LUO XianWen

作者单位: Information Management Department Southwest University Chongqing, China

会议类型: 国际会议

会议名称: 2010 Second Asia-Pacific Conference on Information Processing(2010年第二届亚太地区信息处理国际会议 APCIP 2010)

会议地点: 南昌

会议语种:英文

页码: 327-330

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）