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Scheduling Multiple Yard Cranes with Crane Interference and Safety Distance Requirement

Author

Listed:
  • Yong Wu

    (Department of International Business and Asian Studies, Griffith University, Gold Coast Campus, Southport, QLD 4222, Australia)

  • Wenkai Li

    (Graduate School of International Management, International University of Japan, Niigata 949-7277, Japan)

  • Matthew E. H. Petering

    (Industrial and Manufacturing Engineering Department, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin 53211)

  • Mark Goh

    (NUS Business School and The Logistics Institute–Asia Pacific, National University of Singapore, Singapore 119245; and School of Business Information Technology and Logistics, and Platform Technologies Research Institute, RMIT University, Melbourne, VIC 3000, Australia)

  • Robert de Souza

    (The Logistics Institute–Asia Pacific, National University of Singapore, Singapore 119613)

Abstract

Container terminals require robust scheduling algorithms for yard cranes to optimally determine the sequence of storage and retrieval operations in yard blocks for higher container terminal performance. This paper investigates the multiple yard crane scheduling problem within a generic yard block and considers the operational restrictions such as the crane noncrossing constraint and models the crane travel time realistically. Further, the fact that any two adjacent cranes must keep an operational safety distance is also taken into consideration. These physical constraints limit the mobility of yard cranes and greatly render the scheduling difficulty for such pieces of equipment.This paper proposes a clustering-reassigning approach, which fully considers all of the operational constraints in practice. The complexity of the approach is o ( n 3 ), where n is the number of container moves to be scheduled, making it suitable for real-time scheduling. Numerical experiments and benchmark with a continuous time-based mixed-integer linear programming model indicate that the clustering-reassigning approach can provide satisfactory near optimal solutions for different sets of test cases in a real-time scheduling context.

Suggested Citation

  • Yong Wu & Wenkai Li & Matthew E. H. Petering & Mark Goh & Robert de Souza, 2015. "Scheduling Multiple Yard Cranes with Crane Interference and Safety Distance Requirement," Transportation Science, INFORMS, vol. 49(4), pages 990-1005, November.
  • Handle: RePEc:inm:ortrsc:v:49:y:2015:i:4:p:990-1005
    DOI: 10.1287/trsc.2015.0641
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Yan Zheng & Meixian Xu & Zhaohu Wang & Yujie Xiao, 2023. "A Genetic Algorithm for Integrated Scheduling of Container Handing Systems at Container Terminals from a Low-Carbon Operations Perspective," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    3. Sumin Chen & Qingcheng Zeng & Yushan Hu, 2022. "Scheduling optimization for two crossover automated stacking cranes considering relocation," Operational Research, Springer, vol. 22(3), pages 2099-2120, July.
    4. Ehleiter, Anne & Jaehn, Florian, 2016. "Housekeeping: Foresightful container repositioning," International Journal of Production Economics, Elsevier, vol. 179(C), pages 203-211.
    5. Boysen, Nils & Briskorn, Dirk & Meisel, Frank, 2017. "A generalized classification scheme for crane scheduling with interference," European Journal of Operational Research, Elsevier, vol. 258(1), pages 343-357.
    6. Zhou, Chenhao & Lee, Byung Kwon & Li, Haobin, 2020. "Integrated optimization on yard crane scheduling and vehicle positioning at container yards," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    7. Xiyan Zheng & Chengji Liang & Yu Wang & Jian Shi & Gino Lim, 2022. "Multi-AGV Dynamic Scheduling in an Automated Container Terminal: A Deep Reinforcement Learning Approach," Mathematics, MDPI, vol. 10(23), pages 1-19, December.
    8. Gharehgozli, Amir & Yu, Yugang & de Koster, René & Du, Shaofu, 2019. "Sequencing storage and retrieval requests in a container block with multiple open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 261-284.
    9. Abou Kasm, Omar & Diabat, Ali & Bierlaire, Michel, 2021. "Vessel scheduling with pilotage and tugging considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    10. 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.
    11. Amelie Eilken, 2019. "A decomposition-based approach to the scheduling of identical automated yard cranes at container terminals," Journal of Scheduling, Springer, vol. 22(5), pages 517-541, October.
    12. 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.
    13. Wang, Mengyao & Zhou, Chenhao & Wang, Aihu, 2022. "A cluster-based yard template design integrated with yard crane deployment using a placement heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    14. Lashkari, Shabnam & Wu, Yong & Petering, Matthew E.H., 2017. "Sequencing dual-spreader crane operations: Mathematical formulation and heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 262(2), pages 521-534.
    15. 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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