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Berth allocation and quay crane assignment/scheduling problem under uncertainty: A survey

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  • Rodrigues, Filipe
  • Agra, Agostinho

Abstract

Port terminals play a critical role in the context of world trade since they are the main nodes responsible for connecting sea and land transportation. There are several optimization problems arising in port terminals, and those involving berth allocation are among the most important ones. They constitute the first level of terminal planning operations. As a consequence, the corresponding decisions impact all the subsequent operations in the port terminals. Berth allocation decisions are often integrated with quay crane assignment and/or scheduling decisions. However, the quality of these decisions is greatly affected by unpredictable events that may occur frequently. Since 2006, different approaches have been proposed for solving general berth allocation problems under uncertainty. This paper provides an exhaustive survey of the works published in the literature addressing berth allocation and berth allocation and quay cranes assignment/scheduling problems under uncertainty. The publications are classified into three main classes of approaches: proactive, reactive, and proactive/reactive. An overview of the main methodologies proposed, including stochastic programming, robust optimization, fuzzy programming, and deterministic approaches, is provided. The common sources of uncertainty are identified, and the representation of the uncertain parameters is highlighted. The papers are also classified according to the main objectives to be optimized and the solution methods proposed. We identify several research trends, limitations in the current literature and future research directions.

Suggested Citation

  • Rodrigues, Filipe & Agra, Agostinho, 2022. "Berth allocation and quay crane assignment/scheduling problem under uncertainty: A survey," European Journal of Operational Research, Elsevier, vol. 303(2), pages 501-524.
  • Handle: RePEc:eee:ejores:v:303:y:2022:i:2:p:501-524
    DOI: 10.1016/j.ejor.2021.12.040
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    3. Cheng Hong & Yufang Guo & Yuhong Wang & Tingting Li, 2023. "The Integrated Scheduling Optimization for Container Handling by Using Driverless Electric Truck in Automated Container Terminal," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    4. Wang, Chong & Liu, Kaiyuan & Zhang, Canrong & Miao, Lixin, 2024. "Distributionally robust chance-constrained optimization for the integrated berth allocation and quay crane assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 182(C).
    5. Xufeng Tang & Chang Liu & Xinqi Li & Ying Ji, 2023. "Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency," Sustainability, MDPI, vol. 15(18), pages 1-27, September.
    6. Meixian Jiang & Jiajia Feng & Jian Zhou & Lin Zhou & Fangzheng Ma & Guanghua Wu & Yuqiu Zhang, 2023. "Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    7. Abou Kasm, Omar & Diabat, Ali & Chow, Joseph Y.J., 2023. "Simultaneous operation of next-generation and traditional quay cranes at container terminals," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1110-1125.
    8. João Luiz Marques Andrade & Gustavo Campos Menezes, 2023. "A column generation-based heuristic to solve the integrated planning, scheduling, yard allocation and berth allocation problem in bulk ports," Journal of Heuristics, Springer, vol. 29(1), pages 39-76, February.
    9. Zhen, Lu & Zhuge, Dan & Wang, Shuaian & Wang, Kai, 2022. "Integrated berth and yard space allocation under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 1-27.
    10. Agra, Agostinho & Rodrigues, Filipe, 2022. "Distributionally robust optimization for the berth allocation problem under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 1-24.

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