Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (9): 51-54.

• 理论研究 • Previous Articles     Next Articles

Improved niche Particle Swarm Optimizer in dynamic environment

LI Xiao-yuan,LI Mei-yi,SONG Ling   

  1. Institute of Information Engineering,Xiangtan University,Xiangtan 411105,China
  • Received:2007-07-11 Revised:2007-10-09 Online:2008-03-21 Published:2008-03-21
  • Contact: LI Xiao-yuan

动态环境下一种改进的小生境粒子群算法

李孝源,李枚毅,宋 凌   

  1. 湘潭大学 信息工程学院,湖南 湘潭 411105
  • 通讯作者: 李孝源

Abstract: The purpose of this paper is to present a modified Particle Swarm Optimization(PSO) algorithm applied to the complex dynamic environment.The method presented is defined as Improve Niche Particle Swarm Optimizer(IN-PSO).It can improve the reliability and accuracy while tracking dynamic pole in dynamic environment and avoid converge to a optimality.The environment used in these experiments is generated by Dynamic Function # 1(DF1).The results of the experiments elucidate that IN-PSO is more adaptive than Adaptive Particle Swarm Optimizer(APSO).

Key words: dynamic environment, niche, PSO, DF1

摘要: 为了提高在动态环境下追踪变化的极点的可靠性和精确性的能力,避免算法收敛于一个最优解,提出了一种改进的小生境微粒群算法。使用DF1(Dynamic Function 1)生成的复杂动态环境对这种算法进行了验证,并与经典的APSO(Adaptive Particle Swarm Optimizer)算法进行了对比,实验结果表明了该算法的有效性。

关键词: 动态环境, 小生境, 微粒群算法, DF1