• DocumentCode
    2555925
  • Title

    Ant colony optimization algorithm to solve split delivery vehicle routing problem

  • Author

    Lu-si Sui ; Jia-fu Tang ; Zhendong Pan ; Shu-an Liu

  • Author_Institution
    Key Lab. of Integrated Autom. of Process Ind. of MOE, Northeastern Univ., Shenyang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    997
  • Lastpage
    1001
  • Abstract
    As a combinatorial optimization problem, vehicle routing problem (VRP) is a typical NP-hard problem; an assumption that the demand of customers can not be split is given to the traditional VRP formulation. However, the transportation cost can be reduced by means of splitting the demand of customers in practical logistics operation. This paper solved the split delivery vehicle routing problem (SDVRP) by means of the ant colony algorithm. The integer programming model of the problem is given in this paper, and a corresponding improved ant colony optimization algorithm (ACO) based on characteristic of the problem is designed to solve the problem. Some simulation experiments on this algorithm and in comparison with the traditional VRP are conducted, which show that the proposed ACO algorithm is effective and the SDVRP can reduce more total costs than traditional VRP.
  • Keywords
    combinatorial mathematics; cost reduction; integer programming; logistics; transportation; vehicles; NP-hard problem; ant colony optimization algorithm; combinatorial optimization problem; customer demand; integer programming model; logistics operation; split delivery vehicle routing problem; transportation cost reduction; Algorithm design and analysis; Ant colony optimization; Automation; Costs; Linear programming; Logistics; NP-hard problem; Routing; Transportation; Vehicles; the split delivery vehicle routing problem (SDVRP) ant colony algorithm (ACO) logistic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597462
  • Filename
    4597462