• DocumentCode
    460820
  • Title

    Particle Swarm Optimization with Escape Velocity

  • Author

    Wang, Xiuli ; Wang, Yongji ; Zeng, Haitao ; Zhou, Hui

  • Volume
    1
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    457
  • Lastpage
    460
  • Abstract
    This paper presents a model of particle swarm optimization with escape velocity (EVPSO) in order to overcome premature convergence in the basic particle swarm optimization (PSO). The EVPSO model equips particles with the escape velocity to avoid them trapping into local minima and increase the diversity of population. A simulation study shows that the EVPSO outperforms the basic PSO, especially for high dimension function. The EVPSO model facilitates solving multi-modal optimization problems
  • Keywords
    evolutionary computation; particle swarm optimisation; escape velocity; evolutionary algorithm; multimodal optimization; particle swarm optimization; Clustering algorithms; Convergence; Equations; Evolutionary computation; Optimization methods; Particle swarm optimization; Performance loss;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security, 2006 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    1-4244-0605-6
  • Electronic_ISBN
    1-4244-0605-6
  • Type

    conf

  • DOI
    10.1109/ICCIAS.2006.294176
  • Filename
    4072129
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=460820