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Berth scheduling by customer service differentiation: A multi-objective approach

Author

Listed:
  • Golias, Mihalis M.
  • Boile, Maria
  • Theofanis, Sotirios

Abstract

In this paper the discrete and dynamic berth allocation problem is formulated as a multi-objective combinatorial optimization problem where vessel service is differentiated upon based on priority agreements. A genetic algorithms based heuristic is developed to solve the resulting problem. A number of numerical experiments showed that the heuristic performed well in solving large, real life instances. The heuristic provided a complete set of solutions that enable terminal operators to evaluate various berth scheduling policies and select the schedule that improves operations and customer satisfaction. The proposed algorithm outperformed a state of the art metaheuristic and provided improved results when compared to the weighted approach.

Suggested Citation

  • Golias, Mihalis M. & Boile, Maria & Theofanis, Sotirios, 2009. "Berth scheduling by customer service differentiation: A multi-objective approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 878-892, November.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:6:p:878-892
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    Citations

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    Cited by:

    1. Feng Li & Jiuh-Biing Sheu & Zi-You Gao, 2015. "Solving the Continuous Berth Allocation and Specific Quay Crane Assignment Problems with Quay Crane Coverage Range," Transportation Science, INFORMS, vol. 49(4), pages 968-989, November.
    2. Albert W. Veenstra & Rogier L. A. Harmelink, 2022. "Process mining ship arrivals in port: the case of the Port of Antwerp," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 584-601, September.
    3. 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.
    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. Liu, Changchun, 2020. "Iterative heuristic for simultaneous allocations of berths, quay cranes, and yards under practical situations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    6. Yu, Jingjing & Tang, Guolei & Song, Xiangqun, 2022. "Collaboration of vessel speed optimization with berth allocation and quay crane assignment considering vessel service differentiation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    7. Jingjing Tong & Heather Nachtmann, 2017. "Cargo prioritization and terminal allocation problem for inland waterway disruptions," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 403-427, August.
    8. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "A note on “Berth allocation considering fuel consumption and vessel emissions”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 48-54.
    9. Ursavas, Evrim & Zhu, Stuart X., 2016. "Optimal policies for the berth allocation problem under stochastic nature," European Journal of Operational Research, Elsevier, vol. 255(2), pages 380-387.
    10. Imai, Akio & Nishimura, Etsuko & Papadimitriou, Stratos, 2013. "Marine container terminal configurations for efficient handling of mega-containerships," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 141-158.
    11. Guo, Liming & Zheng, Jianfeng & Liang, Jinpeng & Wang, Shuaian, 2023. "Column generation for the multi-port berth allocation problem with port cooperation stability," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 3-28.
    12. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    13. 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.
    14. Lu Zhen & Ek Peng Chew & Loo Hay Lee, 2011. "An Integrated Model for Berth Template and Yard Template Planning in Transshipment Hubs," Transportation Science, INFORMS, vol. 45(4), pages 483-504, November.
    15. Kaveshgar, Narges & Huynh, Nathan, 2015. "Integrated quay crane and yard truck scheduling for unloading inbound containers," International Journal of Production Economics, Elsevier, vol. 159(C), pages 168-177.
    16. Xin Wen & Qiong Chen & Yu-Qi Yin & Yui-yip Lau, 2023. "Green Vessel Scheduling with Weather Impact and Emission Control Area Consideration," Mathematics, MDPI, vol. 11(24), pages 1-25, December.
    17. Ng, ManWo, 2024. "Repositioning with unreliable carriers: The case of marine chassis equipment at container ports," European Journal of Operational Research, Elsevier, vol. 315(2), pages 777-785.
    18. Awad M. Aljuaid & Mayssa Koubâa & Mohamed Haykal Ammar & Karim Kammoun & Wafik Hachicha, 2024. "Mathematical Programming Formulations for the Berth Allocation Problems in Container Seaport Terminals," Logistics, MDPI, vol. 8(2), pages 1-17, May.
    19. Imai, Akio & Yamakawa, Yukiko & Huang, Kuancheng, 2014. "The strategic berth template problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 77-100.

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