Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (7): 49-51.DOI: 10.3778/j.issn.1002-8331.2009.07.016

• 研究、探讨 • Previous Articles     Next Articles

Particle Swarm Optimization algorithm with Chaotic Inertia Weight adjusting strategy

WU Qiu-bo1,2,WANG Yun-cheng1,ZHAO Qiu-liang3,WU Chang-rong1   

  1. 1.College of Energy,Chengdu University of Technology,Chengdu 610059,China
    2.Geophysical Prospecting Company,CNPC Chuanqing Drilling & Exploration Corporation,Chengdu 610213,China
    3.College of Electromechanical Engineering,Zhejiang Ocean University,Zhoushan,Zhejiang 316000,China
  • Received:2008-06-11 Revised:2008-09-23 Online:2009-03-01 Published:2009-03-01
  • Contact: WU Qiu-bo

混沌惯性权值调整策略的粒子群优化算法

吴秋波1,2,王允诚1,赵秋亮3,吴昌荣1   

  1. 1.成都理工大学 能源学院,成都 610059
    2.中国石油川庆钻探工程公司 地球物理勘探公司,成都 610213
    3.浙江海洋学院 机电工程学院,浙江 舟山 316000
  • 通讯作者: 吴秋波

Abstract: Particle Swarm Optimization algorithm(PSO) is a new intelligent optimization paradigm.The inertia weight is very important to the performance of PSO.Based on analyzing existing inertia weight adjustment strategy,a novel method,Chaotic Inertia Weight strategy(CIW) is proposed,which describes the inertia weight as a chaotic variable.Results of three benchmark functions indicate the PSO with CIW has been significantly improved on convergence speed comparing with other existing methods,while keeping the excellent computational accuracy.

Key words: Particle Swarm Optimization(PSO), inertia weight, chaos

摘要: 粒子群优化算法是一种新颖的智能优化算法。惯性权值对粒子群优化算法的性能有着重要的影响。在分析已有的惯性权值调整策略的基础上,提出了混沌惯性权值调整策略,该策略将惯性权值用一个混沌变量来描述。标准测试函数实验表明,在不影响优化结果精度的情况下,混沌惯性权值调整策略的粒子群优化算法收敛速度较已有方法有了明显的提高。

关键词: 粒子群优化算法, 惯性权值, 混沌