摘要
粒子群优化 (PSO)算法是一种新兴的优化技术 ,其思想来源于人工生命和演化计算理论。PSO通过粒子追随自己找到的最好解和整个群的最好解来完成优化。该算法简单易实现 ,可调参数少 ,已得到广泛研究和应用。详细介绍了PSO的基本原理、各种改进技术及其应用等 。
Particle swarm optimization (PSO) is a new optimization technique originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. PSO can be implemented with ease and few parameters need to be tuned. It has been successfully applied in many areas. In this paper, the basic principles of PSO are introduced at length, and various improvements and applications of PSO are also presented. Finally, some future research directions about PSO are proposed.
出处
《中国工程科学》
2004年第5期87-94,共8页
Strategic Study of CAE
基金
"八六三"高技术资助项目 ( 2 0 0 1AA413 42 0 )
山东省自然科学基金资助项目 ( 2 0 0 3G0 1)
关键词
群体智能
演化算法
粒子群优化
swarm intelligence
evolutionary algorithm
particle swarm optimization
