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SGICT Builds an Optimization-Based System for Daily Berth Planning

Author

Listed:
  • Yi Ding

    (Logistics Research Center, Shanghai Maritime University, Shanghai 200135, China)

  • Shuai Jia

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong)

  • Tianyi Gu

    (Department of Computer Science, University of New Hampshire, Durham, New Hampshire 03824)

  • Chung-Lun Li

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong)

Abstract

In container terminal operations, the allocation of berth-side resources to serve calling vessels is called berth planning. For each vessel, berth planning generally involves determining the time interval for berth stay (i.e., berthing and departure times and the handling of start and end times), the berthing position along the quay, and the number of quay cranes that will be dedicated to handle it. The objectives are to maximize the vessel service levels (i.e., minimize the departure lateness) and minimize operating costs during a planning horizon. In this paper, we describe the implementation of an operations research-based solution at Shanghai Guandong International Container Terminal (SGICT), one of the largest container terminals at the Port of Shanghai, to optimize its daily berth planning. We embed our solution into a decision support system (BAPOPT), which provides SGICT’s planners with effective and executable berth plans. Using BAPOPT, SGICT expects to improve its vessel-handling productivity by at least 15 percent. With the support of BAPOPT, SGICT has started shifting its operational emphasis from reactive real-time dispatching to proactive resource planning, helping to relieve its operations department from a considerable amount of tedious work and improve the efficiency of its planning department.

Suggested Citation

  • Yi Ding & Shuai Jia & Tianyi Gu & Chung-Lun Li, 2016. "SGICT Builds an Optimization-Based System for Daily Berth Planning," Interfaces, INFORMS, vol. 46(4), pages 281-296, August.
    • Handle: RePEc:inm:orinte:v:46:y:2016:i:4:p:281-296
    DOI: 10.1287/inte.2016.0848
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    References listed on IDEAS

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    3. Wu, Lingxiao & Jia, Shuai & Wang, Shuaian, 2020. "Pilotage planning in seaports," European Journal of Operational Research, Elsevier, vol. 287(1), pages 90-105.
    4. Jaap-Jan Steeg & Menno Oudshoorn & Neil Yorke-Smith, 2023. "Berth planning and real-time disruption recovery: a simulation study for a tidal port," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 70-110, March.
    5. Zhen, Lu & Liang, Zhe & Zhuge, Dan & Lee, Loo Hay & Chew, Ek Peng, 2017. "Daily berth planning in a tidal port with channel flow control," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 193-217.
    6. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong, 2023. "A branch-and-price heuristic algorithm for the bunkering operation problem of a liquefied natural gas bunkering station in the inland waterways," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 145-170.
    7. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong & Sheng, Dian, 2021. "Short-term berth planning and ship scheduling for a busy seaport with channel restrictions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    8. Li, Shuqin & Jia, Shuai, 2019. "The seaport traffic scheduling problem: Formulations and a column-row generation algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 158-184.

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