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Truck Appointment Scheduling: A Review of Models and Algorithms

Author

Listed:
  • Maria D. Gracia

    (Faculty of Engineering Tampico, Universidad Autonoma de Tamaulipas, Tampico 89140, Mexico)

  • Julio Mar-Ortiz

    (Faculty of Engineering Tampico, Universidad Autonoma de Tamaulipas, Tampico 89140, Mexico)

  • Manuel Vargas

    (Industrial Engineering Department, Universidad de Santiago de Chile, Santiago 9170124, Chile)

Abstract

This paper provides a comprehensive review of truck appointment scheduling models and algorithms that support truck appointment systems (TASs) at container terminals. TASs have become essential tools for minimizing congestion, reducing wait times, and improving operational efficiency at the port and maritime industry. This review systematically categorizes and evaluates existing models and optimization algorithms, highlighting their strengths, limitations, and applicability in various operational contexts. We explore deterministic, stochastic, and hybrid models, as well as exact, heuristic, and metaheuristic algorithms. By synthesizing the latest advancements and identifying research gaps, this paper offers valuable insights for academics and practitioners aiming to enhance TAS efficiency and effectiveness. Future research directions and potential improvements in model formulation are also discussed.

Suggested Citation

  • Maria D. Gracia & Julio Mar-Ortiz & Manuel Vargas, 2025. "Truck Appointment Scheduling: A Review of Models and Algorithms," Mathematics, MDPI, vol. 13(3), pages 1-25, February.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:3:p:503-:d:1582643
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    References listed on IDEAS

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    1. Namboothiri, Rajeev & Erera, Alan L., 2008. "Planning local container drayage operations given a port access appointment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(2), pages 185-202, March.
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    4. 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.
    5. Ngoc Anh Dung Do & Izabela Ewa Nielsen & Gang Chen & Peter Nielsen, 2016. "A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal," Annals of Operations Research, Springer, vol. 242(2), pages 285-301, July.
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    7. 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.
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    12. Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
    13. Na Li & Gang Chen & Manwo Ng & Wayne K. Talley & Zhihong Jin, 2020. "Optimized appointment scheduling for export container deliveries at marine terminals," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(4), pages 456-478, June.
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