• DocumentCode
    2912404
  • Title

    Impact of tuning parameters on dynamic swarms in PSO-based multiobjective optimization

  • Author

    Leong, Wen-Fung ; Yen, Gary G.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    1317
  • Lastpage
    1324
  • Abstract
    In this paper, the improvement of two design components (swarm growing strategy and objective space compression and expansion strategy) from the existing multiple swarms MOPSO, namely DSMOPSO, is presented. In addition, sensitivity analysis is conducted to study the impact of the five tuning parameters on its performance through two performance metrics. Simulation results show the improved design is robust with respect to the tuning parameters.
  • Keywords
    particle swarm optimisation; PSO-based multiobjective optimization; dynamic swarms; expansion strategy; objective space compression; particle swarm optimization; swarm growing strategy; tuning parameters; Evolutionary computation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4630966
  • Filename
    4630966