• DocumentCode
    3262225
  • Title

    Convergence of ant colony optimization on first-order deceptive systems

  • Author

    Chen, Yixin ; Sun, Haiying

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Washington Univ. in St. Louis, St. Louis, MO
  • fYear
    2008
  • fDate
    26-28 Aug. 2008
  • Firstpage
    158
  • Lastpage
    163
  • Abstract
    Deceptive problems have been considered difficult for ant colony optimization (ACO) and it was believed that ACO will fail to converge to global optima of deceptive problems. This paper presents a convergence analysis of ACO on deceptive systems. This paper proves, for the first time, that ACO can achieve reachability convergence but not asymptotic convergence for a class of first order deceptive systems (FODS) without assuming a minimum pheromone at each iteration. Experimental results confirm the analysis.
  • Keywords
    convergence of numerical methods; optimisation; ant colony optimization; asymptotic convergence; convergence analysis; first-order deceptive systems; global optima; Ant colony optimization; Computer science; Convergence; Genetic algorithms; Stochastic processes; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing, 2008. GrC 2008. IEEE International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-2512-9
  • Electronic_ISBN
    978-1-4244-2513-6
  • Type

    conf

  • DOI
    10.1109/GRC.2008.4664719
  • Filename
    4664719