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An Optimization Approach to Berth Allocation Problems

Author

Listed:
  • Shu-Chuan Chang

    (College of Management, National Taipei University of Technology, Taipei 106344, Taiwan)

  • Ming-Hua Lin

    (Department of Urban Industrial Management and Marketing, University of Taipei, Taipei 111036, Taiwan)

  • Jung-Fa Tsai

    (Department of Business Management, National Taipei University of Technology, Taipei 106344, Taiwan)

Abstract

The berth allocation problem determining the berthing time and position for incoming vessels in port operations has garnered increased attention within the global transportation network. This study focuses on the berth allocation problem with a continuous quay and dynamic vessel arrivals. With the overarching goal of enhancing service quality and optimizing berth utilization rates, this article proposes a mathematical programming model that minimizes the total waiting time of vessels and the overall completion time of vessel service. The formulated model is a mixed-integer linear programming problem that deterministic optimization techniques can globally solve. For large-scale problems, this study develops a genetic algorithm optimization approach to improve computational efficiency in reaching a near-optimal solution. Several numerical experiments are conducted to demonstrate the effectiveness and efficiency of the proposed approach.

Suggested Citation

  • Shu-Chuan Chang & Ming-Hua Lin & Jung-Fa Tsai, 2024. "An Optimization Approach to Berth Allocation Problems," Mathematics, MDPI, vol. 12(5), pages 1-16, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:753-:d:1350184
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    References listed on IDEAS

    as
    1. Lee, Der-Horng & Chen, Jiang Hang & Cao, Jin Xin, 2010. "The continuous Berth Allocation Problem: A Greedy Randomized Adaptive Search Solution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1017-1029, November.
    2. Kim, Kap Hwan & Moon, Kyung Chan, 2003. "Berth scheduling by simulated annealing," Transportation Research Part B: Methodological, Elsevier, vol. 37(6), pages 541-560, July.
    3. Imai, Akio & Nishimura, Etsuko & Papadimitriou, Stratos, 2001. "The dynamic berth allocation problem for a container port," Transportation Research Part B: Methodological, Elsevier, vol. 35(4), pages 401-417, May.
    4. 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.
    5. Jakobs, Stefan, 1996. "On genetic algorithms for the packing of polygons," European Journal of Operational Research, Elsevier, vol. 88(1), pages 165-181, January.
    6. Imai, Akio & Sun, Xin & Nishimura, Etsuko & Papadimitriou, Stratos, 2005. "Berth allocation in a container port: using a continuous location space approach," Transportation Research Part B: Methodological, Elsevier, vol. 39(3), pages 199-221, March.
    7. Yangcan Wu & Lixin Miao & Ya Jia, 2021. "An Efficient Procedure for Inserting Buffers to Generate Robust Berth Plans in Container Terminals," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-9, March.
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    Full references (including those not matched with items on IDEAS)

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