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Real-time container storage location assignment at a seaport container transshipment terminal: dispersion levels, yard templates, and sensitivity analyses

Author

Listed:
  • Matthew E. H. Petering

    (University of Wisconsin—Milwaukee)

  • Yong Wu

    (Griffith University)

  • Wenkai Li

    (International University of Japan)

  • Mark Goh

    (National University of Singapore
    The Logistics Institute-Asia Pacific)

  • Robert Souza

    (The Logistics Institute-Asia Pacific)

  • Katta G. Murty

    (University of Michigan)

Abstract

We present the results of four experiments that link a seaport container terminal’s overall productivity to the system that automatically selects storage locations for export containers in real time as they enter the terminal. Experiment 1 introduces the concept of a container dispersion level and tests the performance of several dispersion levels at various terminals. Experiment 2 considers the math-programming-based yard template concept that has received much attention in recent years. By evaluating yard templates under simulated operating conditions, we provide a link between yard templates and overall terminal productivity that has been absent from previous studies. Experiments 3 and 4 examine how the vessel berthing policy and yard truck traveling speed affect the performance of the storage systems considered in Experiments 1–2. The experiments provide insight into options for real-time decision making at container terminals that is rare in that (1) performance is measured in overall terms and (2) detailed measures of performance for all entities—berths, vessels, groundslots, quay cranes, yard cranes, yard trucks, and containers—involved in every container’s complete lifetime at the terminal are provided.

Suggested Citation

  • Matthew E. H. Petering & Yong Wu & Wenkai Li & Mark Goh & Robert Souza & Katta G. Murty, 2017. "Real-time container storage location assignment at a seaport container transshipment terminal: dispersion levels, yard templates, and sensitivity analyses," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 369-402, December.
    • Handle: RePEc:spr:flsman:v:29:y:2017:i:3:d:10.1007_s10696-016-9247-5
    DOI: 10.1007/s10696-016-9247-5
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    References listed on IDEAS

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    Cited by:

    1. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    2. Feng, Yuanjun & Song, Dong-Ping & Li, Dong, 2022. "Smart stacking for import containers using customer information at automated container terminals," European Journal of Operational Research, Elsevier, vol. 301(2), pages 502-522.
    3. Yang, Lingyi & Ng, Tsan Sheng & Lee, Loo Hay, 2022. "A robust approximation for yard template optimization under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 160(C), pages 21-53.
    4. T. Jonker & M. B. Duinkerken & N. Yorke-Smith & A. Waal & R. R. Negenborn, 2021. "Coordinated optimization of equipment operations in a container terminal," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 281-311, June.
    5. Maria A. M. Trindade & Paulo S. A. Sousa & Maria R. A. Moreira, 2022. "Ramping up a heuristic procedure for storage location assignment problem with precedence constraints," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 646-669, September.
    6. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.

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