• DocumentCode
    2563384
  • Title

    An Adaptive Parameter Control Strategy for Ant Colony Optimization

  • Author

    Ling, Wei-xin ; Luo, Huan-ping

  • fYear
    2007
  • fDate
    15-19 Dec. 2007
  • Firstpage
    142
  • Lastpage
    146
  • Abstract
    proved to be one of the best performing algorithms for NP-hard combinational optimization problems like TSP. Many researchers have been attracted in research for ACO but fewer tuning methodologies have been done on its parameters which influence the algorithm directly. The setting of ACO´s parameters is studied in this paper. The Artificial Fish Swarm Algorithm (AFSA) is introduced to solve the parameter tuning problem, and an adaptive parameter setting strategy is proposed. It´s proved to be effective by the experiment based on TSPLIB test. Keywords: Artificial Fish Swarm Algorithm, Ant Colony Optimization, parameters, TSP
  • Keywords
    Adaptive control; Ant colony optimization; Computational intelligence; Educational institutions; Equations; Marine animals; Programmable control; Robust control; Security; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security, 2007 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    0-7695-3072-9
  • Electronic_ISBN
    978-0-7695-3072-7
  • Type

    conf

  • DOI
    10.1109/CIS.2007.156
  • Filename
    4415319