• DocumentCode
    3041220
  • Title

    An Improved Particle Swarm Algorithm for Search Optimization

  • Author

    Zhi-Jie, Li ; Xiang-Dong, Liu ; Xiao-Dong, Duan ; Cun-Rui, Wang

  • Author_Institution
    Res. Inst. of Nonlinear Inf. Technol., Dalian Nat. Univ., Dalian, China
  • Volume
    1
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    154
  • Lastpage
    158
  • Abstract
    To address the problem of space locus searching, a slowdown particle swarm optimization (SPSO) is proposed to improve the convergence performance of particle swarm from the position viewpoint. The particle swarm in SPSO is divided into many independent sub-swarms to guarantee that particles convergent to different position, since space locus has multiple optimal solutions and requires the convergence of both fitness and position of particle. Furthermore, particle velocity is updated by half according to fitness to achieve the position convergence. The simulation results show the advantage of the proposed slowdown particle swarm optimization-SPSO, which leads to an efficient position convergence.
  • Keywords
    particle swarm optimisation; search problems; particle swarm algorithm; search optimization; slowdown particle swarm optimization; Convergence; Equations; Evolutionary computation; Information technology; Intelligent systems; Linear particle accelerator; Optimization methods; Particle swarm optimization; Performance evaluation; Space technology; Locus; Particle swarm optimization; Simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3571-5
  • Type

    conf

  • DOI
    10.1109/GCIS.2009.40
  • Filename
    5208998