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The selective vehicle routing problem in a collaborative environment


  • DEFRYN, Christof
  • SÖRENSEN, Kenneth
  • CORNELISSENS, Trijntje


We consider a selective vehicle routing problem, in which customers belonging to different partners in a logistic coalition are served in a single logistic operation with multiple vehicles. Each partner determines a cost of non-delivery (CND) for each of its customers, and a central algorithm creates an operational plan, including the decision on which customers to serve and in which trip. The total transportation cost of the coalition is then divided back to the partners through a cost allocation mechanism. This paper investigates the effect on the cost allocation of a partner’s strategy on non-delivery penalties (high/low) and the properties of its customer locations (distance to the depot, degree of clustering). The effect of the cost allocation method used by the coalition is also investigated. We compare the well-known Shapley value cost allocation method to our novel problem-specific method: the CND-weighted cost allocation method. We prove that an adequate cost allocation method can provide an incentive for each partner to behave in a way that benefits the coalition. Further, we develop a transformation that is able to transform any cost allocation into an individually rational one without losing this incentive.

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  • DEFRYN, Christof & SÖRENSEN, Kenneth & CORNELISSENS, Trijntje, 2015. "The selective vehicle routing problem in a collaborative environment," Working Papers 2015006, University of Antwerp, Faculty of Applied Economics.
  • Handle: RePEc:ant:wpaper:2015006

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    References listed on IDEAS

    1. Vansteenwegen, Pieter & Souffriau, Wouter & Berghe, Greet Vanden & Oudheusden, Dirk Van, 2009. "A guided local search metaheuristic for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 118-127, July.
    2. Cruijssen, F.C.A.M. & Salomon, M., 2004. "Empirical Study : Order Sharing Between Transportation Companies may Result in Cost Reductions Between 5 to 15 Percent," Discussion Paper 2004-80, Tilburg University, Center for Economic Research.
    3. Hageback, Charlotte & Segerstedt, Anders, 2004. "The need for co-distribution in rural areas--a study of Pajala in Sweden," International Journal of Production Economics, Elsevier, vol. 89(2), pages 153-163, May.
    4. Dudek, Gregor & Stadtler, Hartmut, 2005. "Negotiation-based collaborative planning between supply chains partners," European Journal of Operational Research, Elsevier, vol. 163(3), pages 668-687, June.
    5. le Blanc, H.M. & Cruijssen, F. & Fleuren, H.A. & de Koster, M.B.M., 2006. "Factory gate pricing: An analysis of the Dutch retail distribution," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1950-1967, November.
    6. Frisk, M. & Göthe-Lundgren, M. & Jörnsten, K. & Rönnqvist, M., 2010. "Cost allocation in collaborative forest transportation," European Journal of Operational Research, Elsevier, vol. 205(2), pages 448-458, September.
    7. Nagarajan, Mahesh & Sosic, Greys, 2008. "Game-theoretic analysis of cooperation among supply chain agents: Review and extensions," European Journal of Operational Research, Elsevier, vol. 187(3), pages 719-745, June.
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    Horizontal collaboration; Selective vehicle routing problem; Collaborative vehicle routing; Cost allocation;

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