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Tighter MIP models for Barge Container Ship Routing

Author

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  • Alfandari, Laurent
  • Davidović, Tatjana
  • Furini, Fabio
  • Ljubić, Ivana
  • Maraš, Vladislav
  • Martin, Sébastien

Abstract

This paper addresses the problem of optimal planning of a liner service for a barge container shipping company. Given estimated weekly demands between pairs of ports, our goal is to determine the subset of ports to be called and the amount of containers to be shipped between each pair of ports, so as to maximize the profit of the shipping company. In order to save possible leasing or storage costs of empty containers at the respective ports, our approach takes into account the repositioning of empty containers. The line has to follow the outbound–inbound principle, starting from the port at the river mouth. We propose a novel integrated approach in which the shipping company can simultaneously optimize the route (along with repositioning of empty containers), the choice of the final port, length of the turnaround time and the size of its fleet. To solve this problem, a new mixed integer programming model is proposed. On the publicly available set of benchmark instances for barge container routing, we demonstrate that this model provides very tight dual bounds and significantly outperforms the existing approaches from the literature for splittable demands.

Suggested Citation

  • Alfandari, Laurent & Davidović, Tatjana & Furini, Fabio & Ljubić, Ivana & Maraš, Vladislav & Martin, Sébastien, 2019. "Tighter MIP models for Barge Container Ship Routing," Omega, Elsevier, vol. 82(C), pages 38-54.
  • Handle: RePEc:eee:jomega:v:82:y:2019:i:c:p:38-54
    DOI: 10.1016/j.omega.2017.12.002
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    References listed on IDEAS

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    1. Krishan Rana & R. G. Vickson, 1988. "A Model and Solution Algorithm for Optimal Routing of a Time-Chartered Containership," Transportation Science, INFORMS, vol. 22(2), pages 83-95, May.
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    Cited by:

    1. Jeong, Yoonjea & Saha, Subrata & Moon, Ilkyeong, 2020. "Optimal devanning time and detention charges for container supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    2. Wu, Dexiang & Dash Wu, Desheng, 2019. "An enhanced decision support approach for learning and tracking derivative index," Omega, Elsevier, vol. 88(C), pages 63-76.
    3. Fazi, Stefano & Fransoo, Jan C. & Van Woensel, Tom & Dong, Jing-Xin, 2020. "A variant of the split vehicle routing problem with simultaneous deliveries and pickups for inland container shipping in dry-port based systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).

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