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Robust bunker management for liner shipping networks

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  • Wang, Shuaian
  • Meng, Qiang

Abstract

This paper examines the sailing speed of containerships and refueling of bunker in a liner shipping network while considering that the real speed may deviate from the planned one. It develops a mixed-integer nonlinear optimization model to minimize the total cost consisting of ship cost, bunker cost, and inventory cost, under the worst-case bunker consumption scenario. A close-form expression for the worst-case bunker consumption is derived and three linearization techniques are proposed to transform the nonlinear model to a mixed-integer linear programming formulation. A case study based on the Asia–Europe–Oceania network of a global liner shipping company demonstrates the applicability of the proposed model and interesting managerial insights are obtained.

Suggested Citation

  • Wang, Shuaian & Meng, Qiang, 2015. "Robust bunker management for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 243(3), pages 789-797.
    • Handle: RePEc:eee:ejores:v:243:y:2015:i:3:p:789-797
    DOI: 10.1016/j.ejor.2014.12.049
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    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. Dan Zhuge & Shuaian Wang & Lu Zhen & Gilbert Laporte, 2021. "Subsidy design in a vessel speed reduction incentive program under government policies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(3), pages 344-358, April.
    6. Zhen, Lu & Wu, Yiwei & Wang, Shuaian & Laporte, Gilbert, 2020. "Green technology adoption for fleet deployment in a shipping network," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 388-410.
    7. 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.
    8. Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2021. "Solving a stochastic inland waterway port management problem using a parallelized hybrid decomposition algorithm," Omega, Elsevier, vol. 102(C).
    9. 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.
    10. Zheng, Jianfeng & Sun, Zhuo & Zhang, Fangjun, 2016. "Measuring the perceived container leasing prices in liner shipping network design with empty container repositioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 123-140.
    11. Ali Cheaitou & Pierre Cariou, 2019. "Greening of maritime transportation: a multi-objective optimization approach," Annals of Operations Research, Springer, vol. 273(1), pages 501-525, February.
    12. Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2020. "A Bender’s based nested decomposition algorithm to solve a stochastic inland waterway port management problem considering perishable product," International Journal of Production Economics, Elsevier, vol. 229(C).
    13. 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.
    14. Junayed Pasha & Maxim A. Dulebenets & Masoud Kavoosi & Olumide F. Abioye & Oluwatosin Theophilus & Hui Wang & Raphael Kampmann & Weihong Guo, 2020. "Holistic tactical-level planning in liner shipping: an exact optimization approach," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-35, December.
    15. 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.
    16. 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.
    17. Nguyen, Son & Fu, Xiuju & Ogawa, Daichi & Zheng, Qin, 2023. "An application-oriented testing regime and multi-ship predictive modeling for vessel fuel consumption prediction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    18. Gang Du & Chuanwang Sun & Jinxian Weng, 2016. "Liner Shipping Fleet Deployment with Sustainable Collaborative Transportation," Sustainability, MDPI, vol. 8(2), pages 1-15, February.
    19. Cui, Qiang & Li, Ye & Lin, Jing-ling, 2018. "Pollution abatement costs change decomposition for airlines: An analysis from a dynamic perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 96-107.
    20. 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.
    21. Ming Liu & Xin Liu & Maoran Zhu & Feifeng Zheng, 2019. "Stochastic Drone Fleet Deployment and Planning Problem Considering Multiple-Type Delivery Service," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    22. 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.

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