• DocumentCode
    236775
  • Title

    Using the Ant Colony Optimization algorithm for the Capacitated Vehicle Routing Problem

  • Author

    Stodola, Petr ; Mazal, Jan ; Podhorec, Milan ; Litvaj, Ondrej

  • Author_Institution
    Univ. of Defence, Brmo, Czech Republic
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    503
  • Lastpage
    510
  • Abstract
    This paper deals with the application of the Ant Colony Optimization (ACO) algorithm to solve the Capacitated Vehicle Routing Problem (CVRP). The first part presents the basic approach and concept which has been inspired by nature. Next, the basic features and parameters of the algorithm are discussed. Then, a number of experiments are introduced which served to verify the algorithm. We chose Christofides, Mingozzi and Toth´s CVRP instances as benchmark problems. The results we obtained are compared with other state-of-the-art algorithms. Next, the improvement of the algorithm is presented. The last part of the paper presents the application of the problem in practice; the primary objective is to plan the distribution of supplies and logistics in the real environment. Finally, the paper summarizes some perspectives of our future work.
  • Keywords
    ant colony optimisation; logistics; vehicle routing; ACO algorithm; CVRP; ant colony optimization algorithm; capacitated vehicle routing problem; Ant colony optimization; Benchmark testing; Classification algorithms; Educational institutions; Multicore processing; Vehicle routing; Vehicles; ant colony optimization; capacitated vehicle routing problem; metaheuristic algorithm; optimal supply distribution; paralel processing; speedup;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics - Mechatronika (ME), 2014 16th International Conference on
  • Conference_Location
    Brno
  • Print_ISBN
    978-80-214-4817-9
  • Type

    conf

  • DOI
    10.1109/MECHATRONIKA.2014.7018311
  • Filename
    7018311