• DocumentCode
    1665608
  • Title

    An improved FSOA based on stochastic search

  • Author

    Wang Yong ; Lu Chuang ; Zhang Xin-zheng

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Guangxi Univ. for Nat., Nanning, China
  • fYear
    2012
  • Firstpage
    1601
  • Lastpage
    1604
  • Abstract
    In order to overcome the shortcoming of being trapped in local minima in basic FSOA(an optimization approach on using fishing strategy), an improving FSOA is presented based on stochastic search. The improving algorithm makes use of the stochastic searh approach and do not adopt the strategy of constricting search. It shows, from the experimental simulation results of some typical benchmark optimization problems and some typical restricted functions optimization problems, that the proposed optimization algorithm not only has great advantages of convergence property over basic FSOA, PSO and GA, but also can effectively avoid being trapped in local minima.
  • Keywords
    convergence; optimisation; search problems; stochastic processes; GA; PSO; constricting search; convergence property; fishing strategy; improved FSOA; local minima; optimization algorithm; optimization approach; restricted function optimization problem; stochastic search; stochastic searh approach; Benchmark testing; Educational institutions; Genetic algorithms; Marine animals; Optimization; Particle swarm optimization; Stochastic processes; FSOA; IFSOA; fishing; optimization algorithm; stochastic search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4673-1871-6
  • Electronic_ISBN
    978-1-4673-1870-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2012.6485386
  • Filename
    6485386