• DocumentCode
    472473
  • Title

    A Multi-Subpopulation Accelerating Particle Swarm Optimization

  • Author

    Jiang, Yi

  • Author_Institution
    Wuhan Univ., Wuhan
  • fYear
    2008
  • fDate
    23-24 Jan. 2008
  • Firstpage
    379
  • Lastpage
    382
  • Abstract
    The particle swarm optimization is a stochastic, population-based optimization technique that can be applied to a wide range of problems. A multi- subpopulation accelerating particle swarm optimization(MAPSO)is proposed to improve the performance of the original algorithm. MAPSO views the excellent individuals as attractors and generates local small populations in the neighbor of them to maintain the diversity of the population. In the course of searching, MAPSO constantly shrinks the searching neighbor and uses the accelerating operators to speed up the evolution of MAPSO. Finally, MAPSO´s efficiency is validated through optimization of benchmark functions.
  • Keywords
    particle swarm optimisation; stochastic processes; multisubpopulation accelerating particle swarm optimization; population-based optimization technique; Acceleration; Birds; Computational intelligence; Computer science; Data mining; Evolutionary computation; Particle swarm optimization; Random sequences; Stochastic processes; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on
  • Conference_Location
    Adelaide, SA
  • Print_ISBN
    978-0-7695-3090-1
  • Type

    conf

  • DOI
    10.1109/WKDD.2008.69
  • Filename
    4470418