• DocumentCode
    2501022
  • Title

    An improved two particles PSO algorithm

  • Author

    Li, Ming ; Yang, Cheng ; Yang, Cheng-wu

  • Author_Institution
    Coll. of Commun., Southwest Forestry Coll., Kunming
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    8743
  • Lastpage
    8748
  • Abstract
    In order to reduce the size and improve the convergence of PSO (particle swarm optimization) algorithm, an improved PSO algorithm, called TPSO (two particles PSO) algorithm, is presented in this paper. The swarm is only composed of two particles in TPSO algorithm. The algorithm is guaranteed to converge to the global optimization solution with probability one. Its global search ability is enhanced through re-initialize the particles at every moment. Executing several stochastic searches continuously around the best position of the swarm can enhance its local search ability. Simulation results show that TPSO algorithm can converge to the global optimization solution of three standard nonlinear test functions rapidly.
  • Keywords
    convergence; nonlinear programming; particle swarm optimisation; probability; search problems; stochastic programming; algorithm convergence; global optimization solution; global search ability; nonlinear test functions; particle swarm optimization; probability; stochastic searches; Automation; Civil engineering; Educational institutions; Forestry; Intelligent control; Machinery; Particle swarm optimization; Power engineering; Stochastic processes; Testing; PSO algorithm; global convergence; two particles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4594306
  • Filename
    4594306