• DocumentCode
    2639361
  • Title

    An Ant Colony Algorithm with Stochastic Local Search for the VRP

  • Author

    Qi, Chengming

  • Author_Institution
    Coll. of Autom., Beijing Union Univ., Beijing
  • fYear
    2008
  • fDate
    18-20 June 2008
  • Firstpage
    464
  • Lastpage
    464
  • Abstract
    In recent years there has been growing interest in algorithms inspired by the observation of natural phenomena to define computational procedures which can solve complex problems. In this paper, through an analysis of the constructive procedure of the solution in the ant colony system (ACS), a vehicle routing problem (VRP) is examined and a hybrid ant colony system coupled with a stochastic local search algorithm(SLSACS), is proposed. In SLSACS, only partial customers are randomly chosen to compute the transition probability. Experiments on various aspects of the algorithm and computational results for fourteen benchmark problems are reported. We compare our approach with ACS, some other classic, powerful meta-heuristics and show that our results are competitive.
  • Keywords
    optimisation; probability; search problems; stochastic processes; transportation; ant colony algorithm; ant colony system; stochastic local search algorithm; transition probability; vehicle routing problem; Algorithm design and analysis; Ant colony optimization; Automation; Cities and towns; Educational institutions; Routing; Stochastic processes; Stochastic systems; Traveling salesman problems; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-0-7695-3161-8
  • Electronic_ISBN
    978-0-7695-3161-8
  • Type

    conf

  • DOI
    10.1109/ICICIC.2008.130
  • Filename
    4603653