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A bi-objective berth allocation formulation to account for vessel handling time uncertainty

Author

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  • Mihalis M Golias

    (Department of Civil Engineering and Center for Intermodal Freight Transportation Studies, University of Memphis, Memphis, Tennessee 38152, USA.)

Abstract

In this article we formulate the berth allocation problem as a bi-objective mixed-integer programming problem with the objective to maximize berth throughput and reliability of the schedule under the assumption that vessel handling times are stochastic parameters, being a function of other stochastic parameters (that is, quay crane breakdowns, quay-to-yard transport vehicle productivity, yard congestion, and so on). A combination of an exact algorithm, a Genetic Algorithms-based heuristic and a Monte Carlo simulation are proposed as the solution approach for the resulting problem. Based on a number of simulation experiments, it is shown that the proposed modeling approach is effective and outperforms berth allocation solutions where reliability is not considered.

Suggested Citation

  • Mihalis M Golias, 2011. "A bi-objective berth allocation formulation to account for vessel handling time uncertainty," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(4), pages 419-441, December.
    • Handle: RePEc:pal:marecl:v:13:y:2011:i:4:p:419-441
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    Citations

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    Cited by:

    1. Buddhi A. Weerasinghe & H. Niles Perera & Xiwen Bai, 2024. "Optimizing container terminal operations: a systematic review of operations research applications," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(2), pages 307-341, June.
    2. 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.
    3. 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.
    4. Xiang, Xi & Liu, Changchun, 2021. "An expanded robust optimisation approach for the berth allocation problem considering uncertain operation time," Omega, Elsevier, vol. 103(C).
    5. Jia, Shuai & Li, Chung-Lun & Xu, Zhou, 2020. "A simulation optimization method for deep-sea vessel berth planning and feeder arrival scheduling at a container port," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 174-196.
    6. Guo, Liming & Zheng, Jianfeng & Du, Haoming & Du, Jian & Zhu, Zhihong, 2022. "The berth assignment and allocation problem considering cooperative liner carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. Xiang, Xi & Liu, Changchun & Miao, Lixin, 2017. "A bi-objective robust model for berth allocation scheduling under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 294-319.
    8. 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.
    9. Changchun Liu & Xi Xiang & Li Zheng, 2020. "A two-stage robust optimization approach for the berth allocation problem under uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 425-452, June.

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