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Scheduling appointments for container truck arrivals considering their effects on congestion

Author

Listed:
  • Sanghyuk Yi

    (University of Bremen)

  • Bernd Scholz-Reiter

    (University of Bremen)

  • Taehoon Kim

    (Pusan National University)

  • Kap Hwan Kim

    (Pusan National University)

Abstract

Trucking companies deliver a large number of containers every day to container terminals at hub ports. Truck drivers for the delivery operation can experience long waiting times when they arrive at peak hours. This study proposes a scheduling method for appointments that considers the cost of trucks staying in the terminal, demurrage cost, container delivery cost, number of appointments allowed at each time window and block, and number of trucks available during each time window. Unlike previous studies, this study considers the effects of the appointments on the waiting time at the terminal when the appointment schedule is constructed. This paper introduces a mathematical formulation and a heuristic algorithm based on the Frank–Wolfe algorithm to solve the problem within a reasonable computational time. Numerical experiments are conducted to compare the proposed algorithm with the other heuristic approaches and analyze the effects of the appointments using empirical data. In addition, the impact of appointments by multiple trucking companies is examined.

Suggested Citation

  • Sanghyuk Yi & Bernd Scholz-Reiter & Taehoon Kim & Kap Hwan Kim, 2019. "Scheduling appointments for container truck arrivals considering their effects on congestion," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 730-762, September.
    • Handle: RePEc:spr:flsman:v:31:y:2019:i:3:d:10.1007_s10696-019-09333-y
    DOI: 10.1007/s10696-019-09333-y
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    References listed on IDEAS

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    1. Schulte, Frederik & Lalla-Ruiz, Eduardo & González-Ramírez, Rosa G. & Voß, Stefan, 2017. "Reducing port-related empty truck emissions: A mathematical approach for truck appointments with collaboration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 195-212.
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    7. Zehendner, Elisabeth & Feillet, Dominique, 2014. "Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal," European Journal of Operational Research, Elsevier, vol. 235(2), pages 461-469.
    8. Chen, Gang & Govindan, Kannan & Yang, Zhongzhen, 2013. "Managing truck arrivals with time windows to alleviate gate congestion at container terminals," International Journal of Production Economics, Elsevier, vol. 141(1), pages 179-188.
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    Citations

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    Cited by:

    1. Afef Lagha & Bechir Ben Daya & Jean-François Audy, 2024. "Assessment of Greenhouse Gas Emissions from Heavy-Duty Trucking in a Non-Containerized Port through Simulation-Based Methods," Sustainability, MDPI, vol. 16(5), pages 1-27, February.
    2. Kjetil Fagerholt & Kap Hwan Kim & Qiang Meng & Julio César Góez & Frank Meisel & Magnus Stålhane, 2019. "Analytics and models for maritime logistics and systems," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 563-566, September.
    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. 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.
    5. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Feng, Xuehao & He, Yucheng & Kim, Kap-Hwan, 2022. "Space planning considering congestion in container terminal yards," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 52-77.
    7. 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).
    8. Mohammad Torkjazi & Nathan Huynh & Ali Asadabadi, 2022. "Modeling the Truck Appointment System as a Multi-Player Game," Logistics, MDPI, vol. 6(3), pages 1-25, July.
    9. Budhi S. Wibowo & Jan C. Fransoo, 2023. "Performance analysis of a drop-swap terminal to mitigate truck congestion at chemical sites," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 416-454, June.

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