An Adaptive Particle Swarm Algorithm for Global Optimization

摘要：

Particle swarm optimization is a relatively new category of meta-heuristic global optimization algorithms. It has been widely concerned by people because of its feasibility and effectiveness. In this paper, an adaptive particle swarm optimization algorithm, which introduces two adaptive acceleration factors in terms of the convergence speed and global search capability of the PSO algorithm, is proposed. A novel weighted function has been introduced and some particles are to be updated in a new way when the proposed algorithm traps in local optimum. The proposed algorithm is shown to enhance the convergence speed and global search capability on different benchmark optimization functions.

关键词： Particle swarm algorithm Meta-heuristic Global optimization

作者: Guo Chonghui Li Hong

作者单位: Institute of Systems Engineering, Dalian University of Technology, P.R.China, 116024 Department of Mathematics, Dalian University of Technology, P.R.China, 116024

会议类型: 国际会议

会议名称: 第六届管理学国际会议(Proceedings of ICM2007 the 6th International on Management)

会议地点: 武汉

会议语种:英文

页码: 8-12

在线出版日期: 2007-08-03（万方平台首次上网日期，不代表论文的发表时间）