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Solving the Liner Shipping Fleet Repositioning Problem with Cargo Flows

Author

Listed:
  • Kevin Tierney

    (IT University of Copenhagen, 2300 Copenhagen S, Denmark; and Department of Business Information Systems, University of Paderborn, 33098 Paderborn, Germany)

  • Björg Áskelsdóttir

    (DTU Management Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

  • Rune Møller Jensen

    (IT University of Copenhagen, 2300 Copenhagen S, Denmark)

  • David Pisinger

    (DTU Management Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

Abstract

We solve a central problem in the liner shipping industry called the liner shipping fleet repositioning problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between routes in a liner shipping network. Liner carriers wish to reposition vessels as cheaply as possible without disrupting cargo flows. The LSFRP is characterized by chains of interacting activities with a multicommodity flow over paths defined by the activities chosen. Despite its industrial importance, the LSFRP has received little attention in the literature. We introduce a novel mathematical model and a simulated annealing algorithm for the LSFRP with cargo flows that makes use of a carefully constructed graph; we evaluate these approaches using real-world data from our industrial collaborator. Additionally, we compare the performance of our approach against an actual repositioning scenario, one of many undertaken by our industrial collaborator in 2011. Our simulated annealing algorithm is able to increase the profit from $18.1 to $31.8 million using only a few minutes of CPU time. This shows that our algorithm could be used in a decision support system to solve the LSFRP.

Suggested Citation

  • Kevin Tierney & Björg Áskelsdóttir & Rune Møller Jensen & David Pisinger, 2015. "Solving the Liner Shipping Fleet Repositioning Problem with Cargo Flows," Transportation Science, INFORMS, vol. 49(3), pages 652-674, August.
    • Handle: RePEc:inm:ortrsc:v:49:y:2015:i:3:p:652-674
    DOI: 10.1287/trsc.2013.0515
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    References listed on IDEAS

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    1. Brouer, Berit D. & Dirksen, Jakob & Pisinger, David & Plum, Christian E.M. & Vaaben, Bo, 2013. "The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping," European Journal of Operational Research, Elsevier, vol. 224(2), pages 362-374.
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    Cited by:

    1. Daniel Müller & Kevin Tierney, 2017. "Decision support and data visualization for liner shipping fleet repositioning," Information Technology and Management, Springer, vol. 18(3), pages 203-221, September.
    2. Purva Grover & Arpan Kumar Kar & Yogesh K. Dwivedi, 2022. "Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions," Annals of Operations Research, Springer, vol. 308(1), pages 177-213, January.
    3. Wetzel, Daniel & Tierney, Kevin, 2020. "Integrating fleet deployment into liner shipping vessel repositioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).

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