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The economic speed of an oceangoing vessel in a dynamic setting

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  • Magirou, Evangelos F.
  • Psaraftis, Harilaos N.
  • Bouritas, Theodore

Abstract

The optimal (economic) speed of oceangoing vessels has become of increased importance due to the combined effect of low freight rates and volatile bunker prices. We examine the problem for vessels operating in the spot market in a tramp mode. In the case of known freight rates between origin destination combinations, a dynamic programming formulation can be applied to determine both the optimal speed and the optimal voyage sequence. Analogous results are derived for random freight rates of known distributions. In the case of independent rates the economic speed depends on fuel price and the expected freight rate, but is independent of the revenue of the particular voyage. For freight rates that depend on a state of the market Markovian random variable, economic speed depends on the market state as well, with increased speed corresponding to good states of the market. The dynamic programming equations in our models differ from those of Markovian decision processes so we develop modifications of standard solution methods, and apply them to small examples.

Suggested Citation

  • Magirou, Evangelos F. & Psaraftis, Harilaos N. & Bouritas, Theodore, 2015. "The economic speed of an oceangoing vessel in a dynamic setting," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 48-67.
    • Handle: RePEc:eee:transb:v:76:y:2015:i:c:p:48-67
    DOI: 10.1016/j.trb.2015.03.001
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    1. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship route schedule design with sea contingency time and port time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 615-633.
    2. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    3. 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.
    4. Jostein Tvedt, 2003. "Shipping market models and the specification of freight rate processes," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 5(4), pages 327-346, December.
    5. Magirou, Vangelis F., 1982. "Stockpiling under price uncertainty and storage capacity constraints," European Journal of Operational Research, Elsevier, vol. 11(3), pages 233-246, November.
    6. Basil A. Kalymon, 1971. "Stochastic Prices in a Single-Item Inventory Purchasing Model," Operations Research, INFORMS, vol. 19(6), pages 1434-1458, October.
    7. Kamal Golabi, 1985. "Optimal Inventory Policies When Ordering Prices are Random," Operations Research, INFORMS, vol. 33(3), pages 575-588, June.
    8. K Fagerholt & G Laporte & I Norstad, 2010. "Reducing fuel emissions by optimizing speed on shipping routes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 523-529, March.
    9. Christos A. Kontovas & Harilaos N. Psaraftis, 2011. "The link between economy and environment in the post-crisis era: lessons learned from slow steaming," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 3(3/4), pages 311-326.
    10. D Ronen, 2011. "The effect of oil price on containership speed and fleet size," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 211-216, January.
    11. Omar Besbes & Sergei Savin, 2009. "Going Bunkers: The Joint Route Selection and Refueling Problem," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 694-711, February.
    12. 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.
    13. Notteboom, Theo E. & Vernimmen, Bert, 2009. "The effect of high fuel costs on liner service configuration in container shipping," Journal of Transport Geography, Elsevier, vol. 17(5), pages 325-337.
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    Cited by:

    1. Harilaos N. Psaraftis, 2019. "Speed Optimization vs Speed Reduction: the Choice between Speed Limits and a Bunker Levy," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    2. Jun Xia & Kevin X. Li & Hong Ma & Zhou Xu, 2015. "Joint Planning of Fleet Deployment, Speed Optimization, and Cargo Allocation for Liner Shipping," Transportation Science, INFORMS, vol. 49(4), pages 922-938, November.
    3. Beullens, Patrick & Ge, Fangsheng & Hudson, Dominic, 2023. "The economic ship speed under time charter contract—A cash flow approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    4. Harilaos N. Psaraftis, 2019. "Speed optimization versus speed reduction: Are speed limits better than a bunker levy?," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(4), pages 524-542, December.
    5. Massimo Giovannini & Harilaos N. Psaraftis, 2019. "The profit maximizing liner shipping problem with flexible frequencies: logistical and environmental considerations," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 567-597, September.
    6. Rau, Philipp & Spinler, Stefan, 2016. "Investment into container shipping capacity: A real options approach in oligopolistic competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 130-147.
    7. Ge, Fangsheng & Beullens, Patrick & Hudson, Dominic, 2021. "Optimal economic ship speeds, the chain effect, and future profit potential," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 168-196.
    8. 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.
    9. Wang, Shuaian & Zhen, Lu & Zhuge, Dan, 2018. "Dynamic programming algorithms for selection of waste disposal ports in cruise shipping," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 235-248.
    10. Harilaos N. Psaraftis, 2019. "Ship routing and scheduling: the cart before the horse conjecture," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(1), pages 111-124, March.
    11. Mallidis, Ioannis & Iakovou, Eleftherios & Dekker, Rommert & Vlachos, Dimitrios, 2018. "The impact of slow steaming on the carriers’ and shippers’ costs: The case of a global logistics network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 18-39.

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