• DocumentCode
    3155070
  • Title

    Mathematical model and solution approach for collaborative logistics in less than truckload (LTL) transportation

  • Author

    Dai, Bo ; Chen, Haoxun

  • Author_Institution
    Ind. Syst. Optimization Lab., Univ. of Technol. of Troyes, Troyes, France
  • fYear
    2009
  • fDate
    6-9 July 2009
  • Firstpage
    767
  • Lastpage
    772
  • Abstract
    Collaborative logistics is achieved when two or more carriers or shippers form partnerships to optimize their transportation operations by sharing vehicle capacities and delivery tasks in order to cut empty back hauls and to increase vehicle utilization rate. This paper studies collaborative logistics in less than truckload transportation and develops a general mathematical model and a Lagrangian relaxation approach to solve this problem. From the model´s optimal solution, a set of feasible vehicle tours corresponding to the transportation operations in collaborative logistics can be constructed. The model is suitable for both shipper collaboration and carrier collaboration. Furthermore, ten randomly generated examples are tested to demonstrate the validity of our proposed model and solution approach.
  • Keywords
    groupware; logistics; mathematical analysis; transportation; vehicles; LTL transportation; Lagrangian relaxation approach; back haul; carrier collaboration; collaborative logistic; delivery task sharing; less than truckload transportation; mathematical model; shipper collaboration; vehicle capacity sharing; vehicle tour set; vehicle utilization rate; Collaboration; Costs; Lagrangian functions; Logistics; Mathematical model; Road transportation; Routing; Shipbuilding industry; Testing; Vehicles; Lagrangian relaxation; collaborative logistics; collaborative transportation management; less than truckload; modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers & Industrial Engineering, 2009. CIE 2009. International Conference on
  • Conference_Location
    Troyes
  • Print_ISBN
    978-1-4244-4135-8
  • Electronic_ISBN
    978-1-4244-4136-5
  • Type

    conf

  • DOI
    10.1109/ICCIE.2009.5223847
  • Filename
    5223847