计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (4): 39-41.DOI: 10.3778/j.issn.1002-8331.2011.04.011

• 研究、探讨 • 上一篇    下一篇

基因变异的群智能优化算法研究

崔明义,张新祥,苏白云   

  1. 河南财经学院 信息学院,郑州 450002
  • 收稿日期:2009-05-05 修回日期:2009-06-25 出版日期:2011-02-01 发布日期:2011-02-01
  • 通讯作者: 崔明义

Research on swarm intelligence optimization based on gene mutation

CUI Mingyi,ZHANG Xinxiang,SU Baiyun   

  1. School of Information,Henan University of Finance & Economics,Zhengzhou 450002,China

  • Received:2009-05-05 Revised:2009-06-25 Online:2011-02-01 Published:2011-02-01
  • Contact: CUI Mingyi

摘要: 粒子群优化(Particle Swarm Optimization,PSO)是一种重要的群智能(Swarm Intelligence,SI)方法。早期收敛和较低的局部搜索能力是PSO的不足。提出一种新颖的基因变异PSO(Gene Mutation PSO,GMPSO),依据概率使粒子的分量发生变异,并做了大量的实验。研究和实验的结果表明,该方法可显著改变PSO的性能,在理论上是可靠的,技术上是可行的。

关键词: 群智能, 粒子群优化, 基因变异

Abstract: Particle Swarm Optimization(PSO) is one of important Swarm Intelligence(SI) methods.The premature convergence and lower local search performance are drawbacks of PSO.This paper proposes a novel Gene Mutation PSO(GMPSO),some components of particles mutate according to the probability,a lot of experiments are taken.The results of the research and experiments indicate that the method can obviously improve the performance of PSO,it is credible in theory and feasible in technique.

Key words: swarm intelligence, particle swarm optimization, gene mutation

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