计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (35): 41-43.DOI: 10.3778/j.issn.1002-8331.2009.35.013

• 研究、探讨 • 上一篇    下一篇

具有量子行为的粒子群优化算法的改进

靳雁霞1,韩 燮2,周汉昌2   

  1. 1.中北大学 电子与计算机科学技术学院,太原 030051
    2.中北大学 仪器科学与动态测试教育部重点实验室,太原 030051
  • 收稿日期:2008-12-25 修回日期:2009-03-03 出版日期:2009-12-11 发布日期:2009-12-11
  • 通讯作者: 靳雁霞

Improved Particle Swarm Optimization algorithm having quantum behavier

JIN Yan-xia1,HAN Xie1,ZHOU Han-chang2   

  1. 1.Department of Computer Science and Technology,North University of China,Taiyuan 030051,China
    2.Key Lab of Instrumentation Science & Dynamic Measurement,Ministry of Education,North University of China,Taiyuan 030051,China
  • Received:2008-12-25 Revised:2009-03-03 Online:2009-12-11 Published:2009-12-11
  • Contact: JIN Yan-xia

摘要: 为改善基本粒子群的全局、局部搜索能力和收敛速度、计算精度,基于标准PSO算法和量子理论基础之上,提出一种改进的基于量子行为的PSO算法—WbQPSO算法。新算法中,采用全同粒子系更新位置,并引入混沌思想,对每个粒子进行混沌搜索,另外通过在Mbesti中加入权重系数,试图改善粒子群的全局、局部搜索能力和收敛速度以及计算精度。对经典函数的测试计算表明:改进算法的性能优于经典的PSO算法,基于量子行为的PSO算法。

Abstract: To improve full searching ability,local searching ability,convergence rate and calculating precision of elementary particle swarm,based on classical PSO(particle swarm optimization) algorithm and quanta theory,this paper proposes an improved PSO algorithm with quantum behavier,WbQPSO algorithm.Indentical particle system is introduced to update the position of particle,chaos thought is introduced to chaotic search every particle and weight coefficient is introduced to Mbesti,accordingly improving the full searching ability,local searching ability,convergence rate and calculating precision of elementary particle swarm.The experimental results of classical function show that capability of improved algorithm is superior to classical algorithm and quantum-behaved PSO algorithm.

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