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Optimization of truck appointments in container terminals

Author

Listed:
  • Xiaoju Zhang

    (Dalian Maritime University)

  • Qingcheng Zeng

    (Dalian Maritime University)

  • Zhongzhen Yang

    (Ningbo University
    National Traffic Management Engineering & Technology Research Centre Ningbo University Sub-centre)

Abstract

Truck appointment has proved to be an efficient tool in reducing congestion at container terminals. To make a reasonable appointment quota plan, it is necessary to take terminal operations into consideration. We develop a novel approach (model) for optimizing a truck appointment system with the objective of decreasing external trucks’ waiting times, at the gate and yard, and internal trucks’ waiting times at the yard. The vacation queuing model is used to describe the coordinated service process of yard cranes. Based on non-stationary queuing theory, truck waiting times are estimated more accurately. Numerical experiments are conducted to illustrate the validity of the model and algorithm. Results show that the model reflects the characteristics of the service process of yard cranes and it improves the calculation accuracy of the truck waiting time.

Suggested Citation

  • Xiaoju Zhang & Qingcheng Zeng & Zhongzhen Yang, 2019. "Optimization of truck appointments in container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(1), pages 125-145, March.
    • Handle: RePEc:pal:marecl:v:21:y:2019:i:1:d:10.1057_s41278-018-0105-0
    DOI: 10.1057/s41278-018-0105-0
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    References listed on IDEAS

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    Cited by:

    1. Li, Dongjun & Dong, Jing-Xin & Song, Dong-Ping & Hicks, Christian & Singh, Surya Prakash, 2020. "Optimal contract design for the exchange of tradable truck permits at multiterminal ports," International Journal of Production Economics, Elsevier, vol. 230(C).
    2. Caballini, Claudia & Gracia, Maria D. & Mar-Ortiz, Julio & Sacone, Simona, 2020. "A combined data mining – optimization approach to manage trucks operations in container terminals with the use of a TAS: Application to an Italian and a Mexican port," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    3. Ahmed M. Abdelmagid & Mohamed Gheith & Amr Eltawil, 2022. "Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times," Logistics, MDPI, vol. 6(3), pages 1-22, July.
    4. Houming Fan & Xiaoxue Ren & Zhenfeng Guo & Yang Li, 2019. "Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    5. Azab, Ahmed & Morita, Hiroshi, 2022. "Coordinating truck appointments with container relocations and retrievals in container terminals under partial appointments information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    6. Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
    7. Lange, Ann-Kathrin & Kreuz, Felix & Langkau, Sven & Jahn, Carlos & Clausen, Uwe, 2020. "Defining the quota of truck appointment systems," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 211-246, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Chen, Rui & Meng, Qiang & Jia, Peng, 2022. "Container port drayage operations and management: Past and future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    9. Serkan Karakas & Mehmet Kirmizi & Batuhan Kocaoglu, 2021. "Yard block assignment, internal truck operations, and berth allocation in container terminals: introducing carbon-footprint minimisation objectives," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(4), pages 750-771, December.
    10. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).

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