• DocumentCode
    2840158
  • Title

    Quantum-Behaved Particle Swarm Optimization with Normal Cloud Mutation Operator

  • Author

    Zhao, Ji ; Sun, Jun ; Xu, Wenbo

  • Author_Institution
    Sch. of Inf. Technol., JiangNan Univ., Wuxi, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The mutation mechanism is introduced into Quantum-behaved Particle Swarm Optimization to increase its global search ability and escape from local minima. Based on the properties of randomness and stable tendency of normal cloud model, this paper proposed a Quantum-behaved Particle Swarm Optimization with Normal Cloud Mutation Operator (QPSO-NCM). This method is tested and compared with particle swarm optimization (PSO), PSO-NCM and QPSO. The experimental results show that QPSO-NCM performs better than the others algorithms.
  • Keywords
    particle swarm optimisation; global search ability; local minima; normal cloud model; normal cloud mutation operator; quantum behaved particle swarm optimization; Clouds; Convergence; Equations; Evolutionary computation; Genetic mutations; Information technology; Particle swarm optimization; Quantum computing; Sun; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5364714
  • Filename
    5364714