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A decision support methodology for strategic planning in maritime transportation

Author

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  • Fagerholt, Kjetil
  • Christiansen, Marielle
  • Magnus Hvattum, Lars
  • Johnsen, Trond A.V.
  • Vabø, Thor J.

Abstract

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.

Suggested Citation

  • Fagerholt, Kjetil & Christiansen, Marielle & Magnus Hvattum, Lars & Johnsen, Trond A.V. & Vabø, Thor J., 2010. "A decision support methodology for strategic planning in maritime transportation," Omega, Elsevier, vol. 38(6), pages 465-474, December.
    • Handle: RePEc:eee:jomega:v:38:y:2010:i:6:p:465-474
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    Cited by:

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    3. 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.
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    6. Jørgen Laake & Abraham Zhang, 2016. "Joint optimization of strategic fleet planning and contract analysis in tramp shipping," Applied Economics, Taylor & Francis Journals, vol. 48(3), pages 203-211, January.
    7. Li, Der-Chiang & Chang, Che-Jung & Chen, Chien-Chih & Chen, Wen-Chih, 2012. "Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case," Omega, Elsevier, vol. 40(6), pages 767-773.
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    11. Said El Noshokaty, 2017. "Shipping Optimisation Systems (SOS): tramp optimisation perspective," Journal of Shipping and Trade, Springer, vol. 2(1), pages 1-36, December.
    12. 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.
    13. Xiaofang Wu & Luoping Zhang & Meifeng Luo, 2020. "Current strategic planning for sustainability in international shipping," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(3), pages 1729-1747, March.
    14. Lev, Benjamin & Kowalski, Krzysztof, 2011. "Modeling fixed-charge problems with polynomials," Omega, Elsevier, vol. 39(6), pages 725-728, December.
    15. 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.
    16. Ksciuk, Jana & Kuhlemann, Stefan & Tierney, Kevin & Koberstein, Achim, 2023. "Uncertainty in maritime ship routing and scheduling: A Literature review," European Journal of Operational Research, Elsevier, vol. 308(2), pages 499-524.
    17. Christiansen, Marielle & Fagerholt, Kjetil & Nygreen, Bjørn & Ronen, David, 2013. "Ship routing and scheduling in the new millennium," European Journal of Operational Research, Elsevier, vol. 228(3), pages 467-483.
    18. Sterna, Malgorzata, 2011. "A survey of scheduling problems with late work criteria," Omega, Elsevier, vol. 39(2), pages 120-129, April.
    19. Hamidreza Eskandari & Ehsan Mahmoodi, 2016. "A simulation-based multi-objective optimization study of the fleet sizing problem in the offshore industry," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(4), pages 436-457, December.
    20. Pache, Hannah & Grafelmann, Michaela & Schwientek, Anne Kathrina & Jahn, Carlos, 2020. "Tactical planning in tramp shipping - A literature review," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 281-308, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    21. Bakkehaug, Rikard & Eidem, Eirik Stamsø & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A stochastic programming formulation for strategic fleet renewal in shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 60-76.
    22. Meng, Qiang & Wang, Shuaian & Lee, Chung-Yee, 2015. "A tailored branch-and-price approach for a joint tramp ship routing and bunkering problem," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 1-19.

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