• DocumentCode
    2831615
  • Title

    Quantum-behaved particle swarm optimization with mutation operator

  • Author

    Liu, Author Jing ; Xu, Author Wenbo ; Sun, Author Jun

  • Author_Institution
    Sch. of Inf. Technol., Southern Yangtze Univ., Wuxi
  • fYear
    2005
  • fDate
    16-16 Nov. 2005
  • Lastpage
    240
  • 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 characteristic of QPSO algorithm, the variable of gbest and mbest is mutated with Cauchy distribution respectively. The experimental results on test functions show that QPSO with gbest and mbest mutation both performs better than PSO and QPSO without mutation
  • Keywords
    mathematical operators; particle swarm optimisation; search problems; statistical distributions; Cauchy distribution; global search ability; mutation operator; quantum-behaved particle swarm optimization; Birds; Convergence; Electronic mail; Evolutionary computation; Genetic mutations; Information technology; Particle swarm optimization; Performance evaluation; Sun; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2488-5
  • Type

    conf

  • DOI
    10.1109/ICTAI.2005.104
  • Filename
    1562943