• DocumentCode
    1602901
  • Title

    A Multi-swarm Based Hybird Optimization Algorithm in Dynamic Environments

  • Author

    Yu, Yan

  • Author_Institution
    Inst. of Comput. Sci. & Inf. Eng., Harbin Normal Univ., Harbin, China
  • Volume
    4
  • fYear
    2010
  • Firstpage
    63
  • Lastpage
    66
  • Abstract
    This paper analyzes the effect of population size to PSO algorithm and proposes Dynamic particle population based particle swarm optimization (DPP-PSO),the core idea of which is that, according to the search, particle swarm dynamically change particle population and gradually decrease the particles with lower search ability when population size are converging constantly and gradually increase new particles to expand the global search ability. The collaborative optimization of these items decrease calculated amount and improve globe exploration ability, which was proved in the test on four benchmark functions.
  • Keywords
    particle swarm optimisation; collaborative optimization; dynamic particle population based particle swarm optimization; global search ability; globe exploration ability; multiswarm based hybrid optimization algorithm; particle population; Algorithm design and analysis; Analytical models; Attenuation; Benchmark testing; Collaboration; Computational modeling; Convergence; Evolutionary computation; Heuristic algorithms; Particle swarm optimization; dynamic particle population; particle swarm optimization algorithm; population; swarm diversity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-1-4244-5642-0
  • Electronic_ISBN
    978-1-4244-5643-7
  • Type

    conf

  • DOI
    10.1109/ICCMS.2010.186
  • Filename
    5421517