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The Block Retrieval Problem

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  • Silva, Marcos de Melo da
  • Erdoğan, Güneş
  • Battarra, Maria
  • Strusevich, Vitaly

Abstract

Retrieving containers from a bay in a port terminal yard is a time consuming activity. The Block Retrieval Problem (BRTP) aims at minimizing the number of relocations, the unproductive moves of hindering containers, while retrieving target containers belonging to a customer. The choice of relocations leads to alternative bay configurations, some of which would minimize the relocations of forthcoming retrievals. The Bi-objective Block Retrieval Problem (2BRTP) includes a secondary objective, the minimization of the expected number of relocations for retrieving the containers of the next customer. This paper provides NP-Hardness proofs for both the BRTP and 2BRTP. A branch-and-bound algorithm and a linear time heuristic are developed for the BRTP; a branch-and-bound algorithm and a beam search algorithm are presented for the 2BRTP. Extensive computational tests on randomly generated instances as well as instances adapted from the literature are performed, and the results are presented.

Suggested Citation

  • Silva, Marcos de Melo da & Erdoğan, Güneş & Battarra, Maria & Strusevich, Vitaly, 2018. "The Block Retrieval Problem," European Journal of Operational Research, Elsevier, vol. 265(3), pages 931-950.
    • Handle: RePEc:eee:ejores:v:265:y:2018:i:3:p:931-950
    DOI: 10.1016/j.ejor.2017.08.048
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    References listed on IDEAS

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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. Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
    4. 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.
    5. Tanaka, Shunji & Voß, Stefan, 2019. "An exact algorithm for the block relocation problem with a stowage plan," European Journal of Operational Research, Elsevier, vol. 279(3), pages 767-781.
    6. Andresson Silva Firmino & Ricardo Martins Abreu Silva & Valéria Cesário Times, 2019. "A reactive GRASP metaheuristic for the container retrieval problem to reduce crane’s working time," Journal of Heuristics, Springer, vol. 25(2), pages 141-173, April.
    7. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Xie, Ying, 2022. "Service fairness and value of customer information for the stochastic container relocation problem under flexible service policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    8. Tanaka, Shunji & Voß, Stefan, 2022. "An exact approach to the restricted block relocation problem based on a new integer programming formulation," European Journal of Operational Research, Elsevier, vol. 296(2), pages 485-503.
    9. 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.

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