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A genetic search-based heuristic for a fleet size and periodic routing problem with application to offshore supply planning

Author

Listed:
  • Thomas Borthen

    (Norwegian University of Science and Technology (NTNU))

  • Henrik Loennechen

    (Norwegian University of Science and Technology (NTNU))

  • Xin Wang

    (Norwegian University of Science and Technology (NTNU))

  • Kjetil Fagerholt

    (Norwegian University of Science and Technology (NTNU)
    SINTEF Ocean)

  • Thibaut Vidal

    (Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio))

Abstract

This paper introduces a genetic search-based heuristic to solve an offshore supply vessel planning problem (SVPP) faced by the Norwegian oil and gas company Statoil. The aim is to help the company in determining the optimal size of supply vessels to charter in and their corresponding voyages and schedules. We take inspiration from the hybrid genetic search with adaptive diversity control (HGSADC) algorithm of Vidal et al. (Oper Res 60(3):611–624, 2012), which successfully addresses a large class of vehicle routing problems, including the multi-period VRP (PVRP), and adapt it to account for some special features that are recurrent in maritime transportation but scarcely found in classical PVRPs, in particular, the possibility of having voyages spanning over multiple time periods in the planning horizon. Our computational experiments show that the proposed heuristic is scalable and stable, being able to solve industrial SVPPs of realistic size while significantly outperforming the existing approaches.

Suggested Citation

  • Thomas Borthen & Henrik Loennechen & Xin Wang & Kjetil Fagerholt & Thibaut Vidal, 2018. "A genetic search-based heuristic for a fleet size and periodic routing problem with application to offshore supply planning," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(2), pages 121-150, June.
    • Handle: RePEc:spr:eurjtl:v:7:y:2018:i:2:d:10.1007_s13676-017-0111-x
    DOI: 10.1007/s13676-017-0111-x
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    References listed on IDEAS

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    1. Thibaut Vidal & Teodor Gabriel Crainic & Michel Gendreau & Nadia Lahrichi & Walter Rei, 2012. "A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems," Operations Research, INFORMS, vol. 60(3), pages 611-624, June.
    2. Norlund, Ellen Karoline & Gribkovskaia, Irina & Laporte, Gilbert, 2015. "Supply vessel planning under cost, environment and robustness considerations," Omega, Elsevier, vol. 57(PB), pages 271-281.
    3. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2014. "A unified solution framework for multi-attribute vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 234(3), pages 658-673.
    4. Halvorsen-Weare, Elin E. & Fagerholt, Kjetil & Nonås, Lars Magne & Asbjørnslett, Bjørn Egil, 2012. "Optimal fleet composition and periodic routing of offshore supply vessels," European Journal of Operational Research, Elsevier, vol. 223(2), pages 508-517.
    5. Bjørnar Aas & Øyvind Halskau Sr & Stein W Wallace, 2009. "The role of supply vessels in offshore logistics," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 11(3), pages 302-325, September.
    6. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    7. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
    8. Fagerholt, Kjetil & Lindstad, Håkon, 2000. "Optimal policies for maintaining a supply service in the Norwegian Sea," Omega, Elsevier, vol. 28(3), pages 269-275, June.
    9. J-F Cordeau & G Laporte & A Mercier, 2001. "A unified tabu search heuristic for vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(8), pages 928-936, August.
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    Cited by:

    1. Vieira, Bruno S. & Ribeiro, Glaydston M. & Bahiense, Laura & Cruz, Roberto & Mendes, André B. & Laporte, Gilbert, 2021. "Exact and heuristic algorithms for the fleet composition and periodic routing problem of offshore supply vessels with berth allocation decisions," European Journal of Operational Research, Elsevier, vol. 295(3), pages 908-923.
    2. Wu, Lingxiao & Wang, Shuaian & Laporte, Gilbert, 2021. "The Robust Bulk Ship Routing Problem with Batched Cargo Selection," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 124-159.
    3. A. M. P. Santos & C. Guedes Soares, 2024. "A hub-location periodic vehicle routing problem in offshore oil and gas logistics," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(4), pages 685-709, December.
    4. Kei Kanamoto & Liwen Murong & Minato Nakashima & Ryuichi Shibasaki, 2021. "Can maritime big data be applied to shipping industry analysis? Focussing on commodities and vessel sizes of dry bulk carriers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 211-236, June.
    5. Santos, A.M.P. & Fagerholt, Kjetil & Laporte, Gilbert & Guedes Soares, C., 2022. "A stochastic optimization approach for the supply vessel planning problem under uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 209-228.
    6. Homsi, Gabriel & Martinelli, Rafael & Vidal, Thibaut & Fagerholt, Kjetil, 2020. "Industrial and tramp ship routing problems: Closing the gap for real-scale instances," European Journal of Operational Research, Elsevier, vol. 283(3), pages 972-990.

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