计算机应用 ›› 2010, Vol. 30 ›› Issue (06): 1516-1518.

• 人工智能 • 上一篇    下一篇

改进的PSO混合算法

杨恢先1,刘子文2,汪俊3,王绪四4,谢鹏鹤3   

  1. 1. 湖南湘潭大学材料与光电物理学院
    2. 湘潭大学信息工程学院
    3.
    4. 湘潭大学材料与光电物理学院
  • 收稿日期:2009-12-23 修回日期:2010-03-07 发布日期:2010-06-01 出版日期:2010-06-01
  • 通讯作者: 杨恢先

Modified PSO hybrid algorithm

  • Received:2009-12-23 Revised:2010-03-07 Online:2010-06-01 Published:2010-06-01

摘要: 为了提高粒子群算法的寻优速度和寻优精度,提出一种改进的PSO混合算法。在差分进化(DE)算法中引入了动态比例因子,在PSO算法中引入DE算法的变异、交叉操作,重新构造PSO算法的粒子位置更新公式。选取了4个基准函数进行测试,并与其他PSO混合算法作了比较。仿真结果表明该方法是有效的。

关键词: 粒子群算法, 差分进化算法, 变异, 交叉

Abstract: This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm. This new algorithm introduced a dynamic proportion operator into differential evolution algorithm and also introduced mutation, crossover operator from DE algorithm into PSO algorithm. Then the position updating formula of PSO was reconstructed. At last, this paper chose four reference functions to have a test and compared the results with other PSO hybrid algorithms. The simulation results verify the effectiveness of this approach.

Key words: PSO algorithm, differential evolution algorithm, mutation, crossover