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Scheduling of Different Automated Yard Crane Systems at Container Terminals

Author

Listed:
  • Ulf Speer

    (Hamburger Hafen und Logistik AG, 20457 Hamburg, Germany)

  • Kathrin Fischer

    (Institute for Operations Research and Information Systems, Hamburg University of Technology, 21073 Hamburg, Germany)

Abstract

In this work, different variants of a branch-and-bound procedure for yard crane scheduling at seaport container terminals and their effect on the terminal’s performance are studied. In particular, this work investigates the level of detail needed to take the exact crane characteristics, e.g., movements and crane interference, into account in the scheduling algorithm. This is examined for four different automated yard crane systems with one or more cranes that operate on rectangular yard blocks with transfer positions at both ends of the block and with the yard blocks arranged orthogonally to the quay. Using a simulation model with realistic scenario data and an automated guided vehicles system for horizontal transport, the results are compared with respect to different key performance indicators, e.g., yard crane productivity and average lateness of jobs. It turns out that especially the consideration of crane interference leads to significant improvements in yard crane productivity. As a result of the long computation times for some crane systems that render the practical application of the algorithm difficult, an approximation procedure is also developed that generates good results in reasonable time and hence allows for real-time application at a container terminal.

Suggested Citation

  • Ulf Speer & Kathrin Fischer, 2017. "Scheduling of Different Automated Yard Crane Systems at Container Terminals," Transportation Science, INFORMS, vol. 51(1), pages 305-324, February.
  • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:1:p:305-324
    DOI: 10.1287/trsc.2016.0687
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    References listed on IDEAS

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    1. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Storage yard operations in container terminals: Literature overview, trends, and research directions," European Journal of Operational Research, Elsevier, vol. 235(2), pages 412-430.
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    Cited by:

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    2. Roy, Debjit & de Koster, René, 2018. "Stochastic modeling of unloading and loading operations at a container terminal using automated lifting vehicles," European Journal of Operational Research, Elsevier, vol. 266(3), pages 895-910.
    3. Dirk Briskorn, 2021. "Routing two stacking cranes with predetermined container sequences," Journal of Scheduling, Springer, vol. 24(4), pages 367-380, August.
    4. 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.
    5. Galle, Virgile & Barnhart, Cynthia & Jaillet, Patrick, 2018. "Yard Crane Scheduling for container storage, retrieval, and relocation," European Journal of Operational Research, Elsevier, vol. 271(1), pages 288-316.
    6. Hang Yu & Yiyun Deng & Leijie Zhang & Xin Xiao & Caimao Tan, 2022. "Yard Operations and Management in Automated Container Terminals: A Review," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
    7. Vallada, Eva & Belenguer, Jose Manuel & Villa, Fulgencia & Alvarez-Valdes, Ramon, 2023. "Models and algorithms for a yard crane scheduling problem in container ports," European Journal of Operational Research, Elsevier, vol. 309(2), pages 910-924.
    8. Lennart Zey & Dirk Briskorn & Nils Boysen, 2022. "Twin-crane scheduling during seaside workload peaks with a dedicated handshake area," Journal of Scheduling, Springer, vol. 25(1), pages 3-34, February.
    9. Dornemann, Jorin & Rückert, Nicolas & Fischer, Kathrin & Taraz, Anusch, 2020. "Artificial intelligence and operations research in maritime logistics," 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 337-381, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    10. Gharehgozli, Amir & Zaerpour, Nima, 2018. "Stacking outbound barge containers in an automated deep-sea terminal," European Journal of Operational Research, Elsevier, vol. 267(3), pages 977-995.
    11. Zhang, Xiaoju & Zeng, Qingcheng & Sheu, Jiuh-Biing, 2019. "Modeling the productivity and stability of a terminal operation system with quay crane double cycling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 181-197.
    12. Shell Ying Huang & Ya Li, 2017. "Yard crane scheduling to minimize total weighted vessel loading time in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 689-720, December.

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