• DocumentCode
    672953
  • Title

    Improved Particle Swarm Optimization for Constrained Optimization

  • Author

    Zhicheng Qu ; Qingyan Li ; Lei Yue

  • Author_Institution
    Tourism Coll., Sichuan Agric. Univ., Dujiangyan, China
  • fYear
    2013
  • fDate
    16-17 Nov. 2013
  • Firstpage
    244
  • Lastpage
    247
  • Abstract
    In this paper, we present an improved particle swarm optimization (PSO) algoritlim to solve constrained optimization problems. The proposed approach, called MPSO, employs a novel mutation operator to enhance the global search ability of PSO. In order to deal with constrains, MPSO uses mean violations mechanism and boundaries search. Simulation results on five famous benchmark problems show that MPSO achieves better results than standard PSO and another variant of PSO.
  • Keywords
    constraint theory; particle swarm optimisation; search problems; MPSO; PSO algorithm; boundary search; constrained optimization problems; global search ability; improved particle swarm optimization algorithm; mean violation mechanism; mutation operator; Benchmark testing; Educational institutions; Optimization; Particle swarm optimization; Sociology; Standards; Statistics; constranined optimization; evolutionary computation; particle swarm optimization (PSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications (ITA), 2013 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-2876-7
  • Type

    conf

  • DOI
    10.1109/ITA.2013.64
  • Filename
    6709980