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Dynamic programming for optimal ship refueling decision

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  • Zhen, Lu
  • Wang, Shuaian
  • Zhuge, Dan

Abstract

This study investigates an optimal control policy for a liner ship to decide at which ports and how much fuel the liner ship should be refueled under stochastic fuel consumption in each leg and stochastic fuel price at each port. Based on some properties proved in this study, a dynamic programming algorithm is then designed to obtain some important threshold values, which are used in the optimal control policy for ship refueling decision. Extensive experiments show that the proposed method can obtain the optimal decision within a reasonable time (about 170s) for various scales of problem instances (up to 30 ports) as well as various settings of probability distributions. In addition, some comparative experiments also show that the proposed optimal decision policy can save at least 8% fuel consumption cost by comparing with some relatively simple rules and save about 1% cost on average by comparing with some brilliantly-designed rules.

Suggested Citation

  • Zhen, Lu & Wang, Shuaian & Zhuge, Dan, 2017. "Dynamic programming for optimal ship refueling decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 63-74.
    • Handle: RePEc:eee:transe:v:100:y:2017:i:c:p:63-74
    DOI: 10.1016/j.tre.2016.12.013
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    1. Hsu, Chaug-Ing & Li, Hui-Chieh & Liu, Su-Miao & Chao, Ching-Cheng, 2011. "Aircraft replacement scheduling: A dynamic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(1), pages 41-60, January.
    2. Lee, L.H. & Lee, C. & Bao, J., 2006. "Inventory control in the presence of an electronic marketplace," European Journal of Operational Research, Elsevier, vol. 174(2), pages 797-815, October.
    3. Ghosh, Sugoutam & Lee, Loo Hay & Ng, Szu Hui, 2015. "Bunkering decisions for a shipping liner in an uncertain environment with service contract," European Journal of Operational Research, Elsevier, vol. 244(3), pages 792-802.
    4. Lindstad, Haakon & Jullumstrø, Egil & Sandaas, Inge, 2013. "Reductions in cost and greenhouse gas emissions with new bulk ship designs enabled by the Panama Canal expansion," Energy Policy, Elsevier, vol. 59(C), pages 341-349.
    5. 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.
    6. Du, Yuquan & Chen, Qiushuang & Quan, Xiongwen & Long, Lei & Fung, Richard Y.K., 2011. "Berth allocation considering fuel consumption and vessel emissions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1021-1037.
    7. Huang, Kuancheng & Liang, Yu-Tung, 2011. "A dynamic programming algorithm based on expected revenue approximation for the network revenue management problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(3), pages 333-341, May.
    8. Qi, Xiangtong & Song, Dong-Ping, 2012. "Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 863-880.
    9. 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.
    10. Wang, Shuaian & Meng, Qiang, 2015. "Robust bunker management for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 243(3), pages 789-797.
    11. Meng, Qiang & Du, Yuquan & Wang, Yadong, 2016. "Shipping log data based container ship fuel efficiency modeling," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 207-229.
    12. Sheng, Xiaoming & Chew, Ek Peng & Lee, Loo Hay, 2015. "(s,S) policy model for liner shipping refueling and sailing speed optimization problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 76-92.
    13. Pedrielli, Giulia & Lee, Loo Hay & Ng, Szu Hui, 2015. "Optimal bunkering contract in a buyer–seller supply chain under price and consumption uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 77-94.
    14. Zhen, Lu & Shen, Tao & Wang, Shuaian & Yu, Shucheng, 2016. "Models on ship scheduling in transshipment hubs with considering bunker cost," International Journal of Production Economics, Elsevier, vol. 173(C), pages 111-121.
    15. 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.
    16. Yuquan Du & Qiushuang Chen & Jasmine Siu Lee Lam & Ya Xu & Jin Xin Cao, 2015. "Modeling the Impacts of Tides and the Virtual Arrival Policy in Berth Allocation," Transportation Science, INFORMS, vol. 49(4), pages 939-956, November.
    17. Christian Edinger Munk Plum & Peter Neergaard Jensen & David Pisinger, 2014. "Bunker purchasing with contracts," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 16(4), pages 418-435, December.
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    Cited by:

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    2. Liqian Yang & Gang Chen & Jinlou Zhao & Niels Gorm Malý Rytter, 2020. "Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping," Sustainability, MDPI, vol. 12(9), pages 1-24, May.
    3. Wu, Lingxiao & Pan, Kai & Wang, Shuaian & Yang, Dong, 2018. "Bulk ship scheduling in industrial shipping with stochastic backhaul canvassing demand," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 117-136.
    4. De, Arijit & Choudhary, Alok & Turkay, Metin & Tiwari, Manoj K., 2021. "Bunkering policies for a fuel bunker management problem for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 289(3), pages 927-939.
    5. Kazemi, Ahmad & Ernst, Andreas T. & Krishnamoorthy, Mohan & Le Bodic, Pierre, 2021. "Locomotive fuel management with inline refueling," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1077-1096.

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