• DocumentCode
    2451025
  • Title

    A New Strategy to Improve Particle Swarm Optimization Exploration Ability

  • Author

    Kessentini, Sameh ; Barchiesi, Dominique

  • Author_Institution
    Group of Autom. Generation of Mesh & Adv. Methods, Univ. of Technol. of Troyes, Troyes, France
  • Volume
    1
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    27
  • Lastpage
    30
  • Abstract
    To improve Particle swarm optimization (PSO) ability to explore new areas without delaying the algorithm convergence, a novel strategy is proposed which consists of choosing the best behavior while the new computed position of particle exceeds the search space. The strategy is tested and compared with conventional ones using adaptive PSO algorithm. Simulation results of benchmark functions are analyzed and show that the new strategy guarantees rapid exploration.
  • Keywords
    particle swarm optimisation; adaptive PSO algorithm; particle swarm optimization exploration ability; search space; Acceleration; Algorithm design and analysis; Convergence; Equations; Mathematical model; Particle swarm optimization; Space exploration; convergence speed; exploration; particle swarm optimization; search space;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.147
  • Filename
    5708705