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Optimizing pre-processing and relocation moves in the Stochastic Container Relocation Problem

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  • Zweers, Bernard G.
  • Bhulai, Sandjai
  • van der Mei, Rob D.

Abstract

In container terminals, containers are often moved to other stacks in order to access containers that need to leave the terminal earlier. We propose a new optimization model in which the containers can be moved in two different phases: a pre-processing and a relocation phase. To solve this problem, we develop an optimal branch-and-bound algorithm. Furthermore, we develop a local search heuristic because the problem is NP-hard. Besides that, we give a rule-based method to estimate the number of relocation moves in a bay. The local search heuristic produces solutions that are close to the optimal solution. Finally, for instances in which the benefits of moving containers in the two different phases are in balance, the solution of the heuristic yields significant improvement compared to the existing methods in which containers are only moved in one of the two phases.

Suggested Citation

  • Zweers, Bernard G. & Bhulai, Sandjai & van der Mei, Rob D., 2020. "Optimizing pre-processing and relocation moves in the Stochastic Container Relocation Problem," European Journal of Operational Research, Elsevier, vol. 283(3), pages 954-971.
    • Handle: RePEc:eee:ejores:v:283:y:2020:i:3:p:954-971
    DOI: 10.1016/j.ejor.2019.11.067
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    Cited by:

    1. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Zeng, Qingcheng, 2020. "The stochastic container relocation problem with flexible service policies," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 116-163.
    2. Azab, Ahmed & Morita, Hiroshi, 2022. "Coordinating truck appointments with container relocations and retrievals in container terminals under partial appointments information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    3. 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.
    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. Huiling Zhu, 2022. "Integrated Containership Stowage Planning: A Methodology for Coordinating Containership Stowage Plan and Terminal Yard Operations," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

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