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A stochastic programming formulation for strategic fleet renewal in shipping

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  • Bakkehaug, Rikard
  • Eidem, Eirik Stamsø
  • Fagerholt, Kjetil
  • Hvattum, Lars Magnus

Abstract

Shipping companies repeatedly face the problem of adjusting their vessel fleet to meet uncertain future transportation demands and compensating for aging vessels. In this paper, a new multi-stage stochastic programming formulation for strategic fleet renewal in shipping is proposed. The new formulation explicitly handles uncertainty in parameters such as future demand, freight rates and vessel prices. Extensive computational tests are performed, comparing different discretizations of the uncertain variables and different lengths of the planning horizon. It is shown that significantly better results are obtained when considering the uncertainty of future parameters, compared to using expected values.

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  • 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.
  • Handle: RePEc:eee:transe:v:72:y:2014:i:c:p:60-76
    DOI: 10.1016/j.tre.2014.09.010
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    1. Tamvakis, Michael N. & Thanopoulou, Helen A., 2000. "Does quality pay? The case of the dry bulk market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 36(4), pages 297-307, December.
    2. Ramchandran Jaikumar & Marius M. Solomon, 1987. "The Tug Fleet Size Problem for Barge Line Operations: A Polynomial Algorithm," Transportation Science, INFORMS, vol. 21(4), pages 264-272, November.
    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. Ovidiu Listes & Rommert Dekker, 2005. "A Scenario Aggregation–Based Approach for Determining a Robust Airline Fleet Composition for Dynamic Capacity Allocation," Transportation Science, INFORMS, vol. 39(3), pages 367-382, August.
    6. 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.
    7. 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.
    8. John M. Mulvey & Hercules Vladimirou, 1992. "Stochastic Network Programming for Financial Planning Problems," Management Science, INFORMS, vol. 38(11), pages 1642-1664, November.
    9. Roar Adland & Steen Koekebakker, 2007. "Ship Valuation Using Cross-Sectional Sales Data: A Multivariate Non-Parametric Approach," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 9(2), pages 105-118, June.
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