• DocumentCode
    2709738
  • Title

    Improving the Performance of Genetic Algorithm in Capacitated Vehicle Routing Problem using Self Imposed Constraints

  • Author

    Ursani, Ziauddin ; Sarker, Ruhul ; Abbass, Hussein A.

  • Author_Institution
    Sch. of Inf. Technol. & Electr. Eng., New South Wales Univ., Canberra, ACT
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    220
  • Lastpage
    225
  • Abstract
    The capacitated vehicle routing problem (CVRP) is a well known member of the family of NP hard problems. In the past few decades, a number of heuristics was introduced to solve this problem but no heuristic can claim to work well in all possible scenarios. In the literature, genetic algorithm (GA) even lags behind the other heuristics. In this paper, we reveal some of the reasons for the inferior performance of GA, and propose a number of mechanisms to improve its performance. A number of test problems are solved to demonstrate the usefulness of the algorithm.
  • Keywords
    computational complexity; constraint theory; genetic algorithms; transportation; vehicles; NP hard problems; capacitated vehicle routing problem; genetic algorithm; self imposed constraints; Australia; Computational intelligence; Genetic algorithms; Information technology; Intelligent vehicles; NP-hard problem; Performance analysis; Processor scheduling; Routing; Vehicle driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Scheduling, 2007. SCIS '07. IEEE Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0704-4
  • Type

    conf

  • DOI
    10.1109/SCIS.2007.367693
  • Filename
    4218620