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Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach

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  • Arslan, Ayşe N.
  • Papageorgiou, Dimitri J.

Abstract

Faced with simultaneous demand and charter cost uncertainty, an industrial shipping company must determine a suitable fleet size, mix, and deployment strategy to satisfy demand. It acquires vessels by time chartering and voyage chartering. Time chartered vessels are acquired for different durations, a decision made before stochastic parameters are known. Voyage charters are procured for a single voyage after uncertain parameters are realized. We introduce the first multi-stage stochastic programming model for the bulk ship fleet renewal problem and solve it in a rolling horizon fashion. Computational results indicate that our approach outperforms traditional methods relying on expected value forecasts.

Suggested Citation

  • Arslan, Ayşe N. & Papageorgiou, Dimitri J., 2017. "Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 69-96.
  • Handle: RePEc:eee:transe:v:97:y:2017:i:c:p:69-96
    DOI: 10.1016/j.tre.2016.10.009
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    1. Giovanni Pantuso & Kjetil Fagerholt & Stein W. Wallace, 2016. "Uncertainty in Fleet Renewal: A Case from Maritime Transportation," Transportation Science, INFORMS, vol. 50(2), pages 390-407, May.
    2. Qiang Meng & Tingsong Wang, 2010. "A chance constrained programming model for short-term liner ship fleet planning problems," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(4), pages 329-346, July.
    3. 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.
    4. Meng, Qiang & Wang, Tingsong, 2011. "A scenario-based dynamic programming model for multi-period liner ship fleet planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(4), pages 401-413, July.
    5. Qiang Meng & Tingsong Wang & Shuaian Wang, 2015. "Multi-period liner ship fleet planning with dependent uncertain container shipment demand," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(1), pages 43-67, January.
    6. M Singer & P Donoso & S Jara, 2002. "Fleet configuration subject to stochastic demand: an application in the distribution of liquefied petroleum gas," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 961-971, September.
    7. 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.
    8. Papageorgiou, Dimitri J. & Nemhauser, George L. & Sokol, Joel & Cheon, Myun-Seok & Keha, Ahmet B., 2014. "MIRPLib – A library of maritime inventory routing problem instances: Survey, core model, and benchmark results," European Journal of Operational Research, Elsevier, vol. 235(2), pages 350-366.
    9. 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.
    10. 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.
    11. List, George F. & Wood, Bryan & Nozick, Linda K. & Turnquist, Mark A. & Jones, Dean A. & Kjeldgaard, Edwin A. & Lawton, Craig R., 2003. "Robust optimization for fleet planning under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 209-227, May.
    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. Meng, Qiang & Wang, Tingsong & Wang, Shuaian, 2012. "Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand," European Journal of Operational Research, Elsevier, vol. 223(1), pages 96-105.
    14. Shyshou, Aliaksandr & Gribkovskaia, Irina & Barceló, Jaume, 2010. "A simulation study of the fleet sizing problem arising in offshore anchor handling operations," European Journal of Operational Research, Elsevier, vol. 203(1), pages 230-240, May.
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