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The Joint Network Vehicle Routing Game

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  • van Zon, M.
  • Spliet, R.
  • van den Heuvel, W.

Abstract

Collaborative transportation can significantly reduce transportation costs as well as greenhouse gas emissions. However, allocating the cost to the collaborating companies remains difficult. We consider the cost-allocation problem which arises when companies, each with multiple delivery locations, collaborate by consolidating demand and combining delivery routes. We model the corresponding cost-allocation problem as a cooperative game: the joint network vehicle routing game (JNVRG). We propose a row generation algorithm to determine a core allocation for the JNVRG. In this approach, we encounter a row generation subproblem which we model as a new variant of a vehicle routing problem with profits. Moreover, we propose two main acceleration strategies for the row generation algorithm. First, we generate rows by relaxing the row generation subproblem, exploiting the tight LP bounds for our formulation of the row generation subproblem. Secondly, we propose to also solve the row generation subproblem heuristically and to only solve it to optimality when the heuristic fails. We demonstrate the effectiveness of the proposed row generation algorithm and the acceleration strategies by means of numerical experiments for both the JNVRG as well as the traditional vehicle routing game, which is a special case of the JNVRG. We create and solve instances based on benchmark instances of the capacitated vehicle routing problem from the literature, ranging from 5 companies with a total of 79 delivery locations to 53 companies with a total of 53 delivery locations.

Suggested Citation

  • van Zon, M. & Spliet, R. & van den Heuvel, W., 2019. "The Joint Network Vehicle Routing Game," Econometric Institute Research Papers EI2019-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:115273
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    Cited by:

    1. Schlicher, L. & Dietzenbacher, Bas & Musegaas, Marieke, 2023. "Stable streaming platforms: a cooperative game approach," Research Memorandum 001, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Chen, Shukai & Wang, Hua & Meng, Qiang, 2023. "Cost allocation of cooperative autonomous truck platooning: Efficiency and stability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 119-141.
    3. Soriano, Adria & Gansterer, Margaretha & Hartl, Richard F., 2023. "The multi-depot vehicle routing problem with profit fairness," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Soriano, Adria & Gansterer, Margaretha & Hartl, Richard F., 2022. "Reprint of: The multi-depot vehicle routing problem with profit fairness," International Journal of Production Economics, Elsevier, vol. 250(C).
    5. van Zon, M. & Spliet, R. & van den Heuvel, W., 2021. "The effect of algorithm capabilities on cooperative games," Econometric Institute Research Papers EI2021-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    More about this item

    Keywords

    Collaborative transportation; Cooperative game theory; Vehicle Routing; Row generation; Vehicle; routing with profits; Branch-and-cut-and-price;
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