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The shore power deployment problem for maritime transportation

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  • Wu, Lingxiao
  • Wang, Shuaian

Abstract

In this paper, we study a shore power deployment problem in a container shipping network. The aim of the problem is to develop a subsidy program for a government that achieves the utmost reduction of at-berth emissions from ships in the network. We formulate the problem as a mathematical model that captures the involved relationships among the government, container ports, and shipping lines. The model is hard to solve because it involves a multi-phase process that does not have a closed-form solution. To solve the problem, we develop a tailored labeling algorithm. Extensive numerical experiments are conducted, and the results demonstrate the applicability and efficiency of the solution method for solving practical instances. The results also demonstrate that the solutions delivered by our algorithm to the problem can significantly reduce the at-berth emissions from ships in the shipping network.

Suggested Citation

  • Wu, Lingxiao & Wang, Shuaian, 2020. "The shore power deployment problem for maritime transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:transe:v:135:y:2020:i:c:s1366554518300218
    DOI: 10.1016/j.tre.2020.101883
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    References listed on IDEAS

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    1. Winkel, R. & Weddige, U. & Johnsen, D. & Hoen, V. & Papaefthimiou, S., 2016. "Shore Side Electricity in Europe: Potential and environmental benefits," Energy Policy, Elsevier, vol. 88(C), pages 584-593.
    2. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    3. Ng, ManWo, 2017. "Revisiting a class of liner fleet deployment models," European Journal of Operational Research, Elsevier, vol. 257(3), pages 773-776.
    4. Song, Dong-Ping & Lyons, Andrew & Li, Dong & Sharifi, Hossein, 2016. "Modeling port competition from a transport chain perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 75-96.
    5. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
    6. Ng, ManWo & Lin, Dung-Ying, 2018. "Fleet deployment in liner shipping with incomplete demand information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 184-189.
    7. Itf, 2019. "Maritime Subsidies: Do They Provide Value for Money?," International Transport Forum Policy Papers 70, OECD Publishing.
    8. Bierwirth, Christian & Meisel, Frank, 2015. "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 244(3), pages 675-689.
    9. Qu, Xiaobo & Meng, Qiang, 2012. "The economic importance of the Straits of Malacca and Singapore: An extreme-scenario analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 258-265.
    10. Zhang, Dong & Liu, Yang & He, Shuangchi, 2019. "Vehicle assignment and relays for one-way electric car-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 125-146.
    11. 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.
    12. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    13. Dong, Jing-Xin & Song, Dong-Ping, 2009. "Container fleet sizing and empty repositioning in liner shipping systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 860-877, November.
    14. Meng, Qiang & Wang, Shuaian, 2012. "Liner ship fleet deployment with week-dependent container shipment demand," European Journal of Operational Research, Elsevier, vol. 222(2), pages 241-252.
    15. Kim, Kap Hwan & Park, Young-Man, 2004. "A crane scheduling method for port container terminals," European Journal of Operational Research, Elsevier, vol. 156(3), pages 752-768, August.
    16. Wang, Shuaian & Meng, Qiang, 2012. "Sailing speed optimization for container ships in a liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 701-714.
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