• DocumentCode
    3397048
  • Title

    A novel concurrent particle swarm optimization

  • Author

    Baskar, S. ; Suganthan, P.N.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • Volume
    1
  • fYear
    2004
  • fDate
    19-23 June 2004
  • Firstpage
    792
  • Abstract
    In this paper, a concurrent PSO (CONPSO) algorithm is proposed to alleviate the premature convergence problem of PSO algorithm. It is a type of parallel algorithm in which modified PSO and FDR-PS algorithms are simulated concurrently with frequent message passing between them. This algorithm avoids the possible crosstalk effect of pbest and gbest terms with nbest term in FDR-PSO. Thereby, search efficiency of proposed algorithm is improved. In order to demonstrate the effectiveness of the proposed algorithm, experiments were conducted on six benchmarks continuous optimization problems. Results clearly demonstrate the superior performance of the proposed algorithm in terms of solution quality, average computation time and consistency. This algorithm is very much suitable for the implementation in parallel computer.
  • Keywords
    convergence; evolutionary computation; message passing; optimisation; parallel algorithms; concurrent particle swarm optimization; continuous optimization problems; convergence problem; evolutionary computation; message passing; parallel algorithm; parallel computers; Birds; Clustering algorithms; Concurrent computing; Educational institutions; Evolutionary computation; Marine animals; Message passing; Parallel algorithms; Particle swarm optimization; Performance analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2004. CEC2004. Congress on
  • Print_ISBN
    0-7803-8515-2
  • Type

    conf

  • DOI
    10.1109/CEC.2004.1330940
  • Filename
    1330940