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A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach

Author

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  • Arijit De

    (Newcastle University)

  • Saurabh Pratap

    (Indian Institute of Information Technology, Design and Manufacturing Jabalpur)

  • Akhilesh Kumar

    (Indian Institute of Technology Kharagpur)

  • M. K. Tiwari

    (Indian Institute of Technology Kharagpur)

Abstract

This paper investigates the dynamic ship berth allocation problem for a container handling port, focusing on vessel waiting time at the anchorage due to the unavailability of the berth and quay cranes. A mixed integer linear programming model considering the fuel cost associated with waiting time and operational time of the docked vessel is developed. The hiring of the quay cranes to load/unload the containers from the ship and arrangement of the vessels in different berths is taken into account. Fuel consumed by the vessels while performing their respective port operations is incorporated in the model for addressing the sustainability aspects in berth allocation problem. A chemical reaction optimization algorithm is proposed to solve the problem in a large-scale realistic environment and compared with the results with block-based genetic algorithm, genetic algorithm and particle swarm optimization. The computational experiment illustrates and validates the proposed model on a real case scenario of the port located in India. The case shows that the developed model achieves better utilization of port resources and available berths.

Suggested Citation

  • Arijit De & Saurabh Pratap & Akhilesh Kumar & M. K. Tiwari, 2020. "A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach," Annals of Operations Research, Springer, vol. 290(1), pages 783-811, July.
    • Handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-3070-1
    DOI: 10.1007/s10479-018-3070-1
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    References listed on IDEAS

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    2. 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.
    3. Ayman Nagi & Meike Schroeder & Wolfgang Kersten, 2021. "Risk Management in Seaports: A Community Analysis at the Port of Hamburg," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    4. Xiaofang Wu & Hsi-Chi Yang, 2021. "An Ecological Sustainability Assessment Approach for Strategic Decision Making in International Shipping," Sustainability, MDPI, vol. 13(20), pages 1-18, October.
    5. 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.
    6. 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.
    7. Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.

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