A Modified Quantum-Behaved Particle Swarm Optimization

  • Jun Sun
  • C. -H. Lai
  • Wenbo Xu
  • Yanrui Ding
  • Zhilei Chai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4487)

Abstract

Based on the previously introduced Quantum-behaved Particle Swarm Optimization (QPSO), a revised QPSO with Gaussian disturbance on the mean best position of the swarm is proposed. The reason for the introduction of this novel method is that the disturbance can effectively prevent the stagnation of the particles and therefore make them escape the local optima and sub-optima more easily. Before proposing the Revised QPSO (RQPSO), we introduce the origin and the development of the original PSO and QPSO. To evaluate the performance of the new method, the Revised QPSO, along with QPSO and Standard PSO, is tested on several well-known benchmark functions. The experimental results show that the Revised QPSO has better performance than QPSO and Standard PSO generally.

Keywords

Global Optimization Swarm Intelligence Particle Swarm Quantum-behaved Particle Swarm and Gaussian distribution 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Jun Sun
    • 1
  • C. -H. Lai
    • 2
  • Wenbo Xu
    • 1
  • Yanrui Ding
    • 1
  • Zhilei Chai
    • 1
  1. 1.Center of Intelligent and High Performance Computing, School of Information Technology, Southern Yangtze University, No. 1800, Lihudadao Road, Wuxi, 214122 JiangsuChina
  2. 2.School of Computing and Mathematical Sciences, University of Greenwich, Greenwich, London SE10 9LSUK

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