IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v100y2017icp63-74.html
   My bibliography  Save this article

Dynamic programming for optimal ship refueling decision

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554516304641
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2016.12.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Yadong & Meng, Qiang, 2021. "Optimizing freight rate of spot market containers with uncertainties in shipping demand and available ship capacity," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 314-332.
    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.
    6. Meng, Bin & Wei, Bangguo & Yang, Mo & Kuang, Haibo, 2023. "Measuring the time-frequency spillover effect among carbon markets and shipping energy markets: A global perspective," Energy Economics, Elsevier, vol. 128(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mulder, J. & Dekker, R., 2016. "Optimization in container liner shipping," Econometric Institute Research Papers EI2016-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Wang, Shuaian & Wang, Xinchang, 2016. "A polynomial-time algorithm for sailing speed optimization with containership resource sharing," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 394-405.
    3. Tan, Roy & Duru, Okan & Thepsithar, Prapisala, 2020. "Assessment of relative fuel cost for dual fuel marine engines along major Asian container shipping routes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    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. Wang, Shuaian & Meng, Qiang, 2015. "Robust bunker management for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 243(3), pages 789-797.
    6. 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.
    7. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.
    8. Dulebenets, Maxim A., 2018. "A comprehensive multi-objective optimization model for the vessel scheduling problem in liner shipping," International Journal of Production Economics, Elsevier, vol. 196(C), pages 293-318.
    9. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    10. 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.
    11. Gu, Yewen & Wallace, Stein W. & Wang, Xin, 2016. "Integrated maritime bunker management with stochastic fuel prices and new emission regulations," Discussion Papers 2016/13, Norwegian School of Economics, Department of Business and Management Science.
    12. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "Bunker consumption optimization methods in shipping: A critical review and extensions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 49-62.
    13. Wang, Hua & Wang, Shuaian & Meng, Qiang, 2014. "Simultaneous optimization of schedule coordination and cargo allocation for liner container shipping networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 261-273.
    14. Wang, Ying & Yeo, Gi-Tae & Ng, Adolf K.Y., 2014. "Choosing optimal bunkering ports for liner shipping companies: A hybrid Fuzzy-Delphi–TOPSIS approach," Transport Policy, Elsevier, vol. 35(C), pages 358-365.
    15. Wang, Shuaian & Wang, Hua & Meng, Qiang, 2015. "Itinerary provision and pricing in container liner shipping revenue management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 135-146.
    16. Wang, Shuaian, 2013. "Essential elements in tactical planning models for container liner shipping," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 84-99.
    17. Aydin, N. & Lee, H. & Mansouri, S.A., 2017. "Speed optimization and bunkering in liner shipping in the presence of uncertain service times and time windows at ports," European Journal of Operational Research, Elsevier, vol. 259(1), pages 143-154.
    18. Maxim A. Dulebenets & Junayed Pasha & Olumide F. Abioye & Masoud Kavoosi, 2021. "Vessel scheduling in liner shipping: a critical literature review and future research needs," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 43-106, March.
    19. 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.
    20. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "Containership scheduling with transit-time-sensitive container shipment demand," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 68-83.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:100:y:2017:i:c:p:63-74. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.