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Berth Allocation Planning Optimization in Container Terminals

In: Supply Chain Analysis

Author

Listed:
  • Jam Dai

    (Georgia Institute of Technology)

  • Wuqin Lin

    (Georgia Institute of Technology)

  • Rajeeva Moorthy

    (Georgia Institute of Technology)

  • Chung-Piaw Teo

    (National University of Singapore)

Abstract

We study the problem of allocating berth space for vessels in container terminals, which is referred to as the berth allocation planning problem. We solve the static berth allocation planning problem as a rectangle packing problem with release time constraints, using a local search algorithm that employs the concept of sequence pair to define the neighborhood structure. We embed this approach in a real time scheduling system to address the berth allocation planning problem in a dynamic environment. We address the issues of vessel allocation to the terminal (thus affecting the overall berth utilization), choice of planning time window (how long to plan ahead in the dynamic environment), and the choice of objective used in the berthing algorithm (e.g., should we focus on minimizing vessels’ waiting time or maximizing berth utilization?). In a moderate load setting, extensive simulation results show that the proposed berthing system is able to allocate space to most of the calling vessels upon arrival, with the majority of them allocated the preferred berthing location. In a heavy load setting, we need to balance the concerns of throughput with acceptable waiting time experienced by vessels. We show that, surprisingly, these can be handled by deliberately delaying berthing of vessels in order to achieve higher throughput in the berthing system.

Suggested Citation

  • Jam Dai & Wuqin Lin & Rajeeva Moorthy & Chung-Piaw Teo, 2008. "Berth Allocation Planning Optimization in Container Terminals," International Series in Operations Research & Management Science, in: Christopher S. Tang & Chung-Piaw Teo & Kwok-Kee Wei (ed.), Supply Chain Analysis, pages 69-104, Springer.
  • Handle: RePEc:spr:isochp:978-0-387-75240-2_4
    DOI: 10.1007/978-0-387-75240-2_4
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    Citations

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    Cited by:

    1. Xavier Schepler & Nabil Absi & Dominique Feillet & Eric Sanlaville, 2019. "The stochastic discrete berth allocation problem," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(4), pages 363-396, December.
    2. Bierwirth, Christian & Meisel, Frank, 2010. "A survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 202(3), pages 615-627, May.
    3. Shangyao Yan & Chung-Cheng Lu & Jun-Hsiao Hsieh & Han-Chun Lin, 2019. "A Dynamic and Flexible Berth Allocation Model with Stochastic Vessel Arrival Times," Networks and Spatial Economics, Springer, vol. 19(3), pages 903-927, September.
    4. Shih-Wei Lin & Ching-Jung Ting & Kun-Chih Wu, 2018. "Simulated annealing with different vessel assignment strategies for the continuous berth allocation problem," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 740-763, December.
    5. Xu, Dongsheng & Li, Chung-Lun & Leung, Joseph Y.-T., 2012. "Berth allocation with time-dependent physical limitations on vessels," European Journal of Operational Research, Elsevier, vol. 216(1), pages 47-56.
    6. Umang, Nitish & Bierlaire, Michel & Vacca, Ilaria, 2013. "Exact and heuristic methods to solve the berth allocation problem in bulk ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 54(C), pages 14-31.
    7. Kastner, Marvin & Pache, Hannah & Jahn, Carlos, 2019. "Simulation-based optimization at container terminals: A literature review," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 112-135, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Changchun Liu & Xi Xiang & Li Zheng, 2017. "Two decision models for berth allocation problem under uncertainty considering service level," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 312-344, December.
    9. Robenek, Tomáš & Umang, Nitish & Bierlaire, Michel & Ropke, Stefan, 2014. "A branch-and-price algorithm to solve the integrated berth allocation and yard assignment problem in bulk ports," European Journal of Operational Research, Elsevier, vol. 235(2), pages 399-411.
    10. Changchun Liu & Xi Xiang & Canrong Zhang & Li Zheng, 2016. "A Decision Model for Berth Allocation Under Uncertainty Considering Service Level Using an Adaptive Differential Evolution Algorithm," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(06), pages 1-28, December.

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