计算机与现代化 ›› 2009, Vol. 1 ›› Issue (7): 22-25.doi: 10.3969/j.issn.1006-2475.2009.07.006

• 人工智能 • 上一篇    下一篇

粒子群优化算法的分析与研究

王 瑾;张求明;黄 波   

  1. 中国地质大学计算机学院,湖北 武汉 430074
  • 收稿日期:2008-07-04 修回日期:1900-01-01 出版日期:2009-07-10 发布日期:2009-07-10

Analysis and Research on Particle Swarm Optimization Algorithm

WANG Jin; ZHANG Qiu-ming; HUANG Bo   

  1. School of Computer, China University of Geosciences, Wuhan 430074, China
  • Received:2008-07-04 Revised:1900-01-01 Online:2009-07-10 Published:2009-07-10

摘要: 粒子群优化算法是一种新兴的基于群智能的演化计算方法,其思想来源于对鸟群运动行为的研究。群体中的每一个粒子通过追随个体最优解和群体最优解来完成解的迭代过程。首先介绍了PSO算法的基本原理,然后对PSO的几种典型改进算法进行了介绍并通过仿真实验对各种算法进行了分析和比对,最后对粒子群算法研究方向进行了展望。

关键词: 粒子群优化, 群智能, 演化

Abstract: Particle swarm optimization algorithm is a kind of new evolutionary computation technology. The algorithm completes the iterative process through following the personal best solution and the global best value. The basic principles of PSO are introduced firstly. Then several typical improved algorithms of PSO are introduced and analyzed and compared by simulation experiment. Finally, future research issues are given.

Key words: particle swarm optimization, swarm intelligence, evolutionary computation

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