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A matheuristic for a multimodal long haul routing problem

Author

Listed:
  • David Wolfinger

    (University of Vienna
    University of Vienna)

  • Fabien Tricoire

    (University of Vienna
    Johannes Kepler University)

  • Karl F. Doerner

    (University of Vienna
    University of Vienna
    Data Science @ University of Vienna)

Abstract

We address a planning problem faced by logistics service providers who transport freight over long distances. Given a set of transportation requests, where the origin and the destination of each request are located far apart from each other, a logistics service provider must find feasible vehicle routes to fulfil those requests at minimum cost. When transporting freight over long distances, multimodal transportation provides a viable alternative to traditional unimodal road transportation. We introduce this new problem, which we call the multimodal long haul routing problem (MMLHRP), and present a mathematical formulation for it. Furthermore, we propose a matheuristic, using iterated local search within a column generation framework, for solving the MMLHRP. Results show that large cost savings can be achieved through multimodal transportation compared to unimodal road transportation.

Suggested Citation

  • David Wolfinger & Fabien Tricoire & Karl F. Doerner, 2019. "A matheuristic for a multimodal long haul routing problem," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(4), pages 397-433, December.
    • Handle: RePEc:spr:eurjtl:v:8:y:2019:i:4:d:10.1007_s13676-018-0131-1
    DOI: 10.1007/s13676-018-0131-1
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    References listed on IDEAS

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    2. Arnau, Quim & Barrena, Eva & Panadero, Javier & de la Torre, Rocio & Juan, Angel A., 2022. "A biased-randomized discrete-event heuristic for coordinated multi-vehicle container transport across interconnected networks," European Journal of Operational Research, Elsevier, vol. 302(1), pages 348-362.

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