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An algorithm with performance guarantee for the Online Container Relocation Problem

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  • Zehendner, Elisabeth
  • Feillet, Dominique
  • Jaillet, Patrick

Abstract

This paper introduces and investigates the Online Container Relocation Problem, where containers have to be retrieved from a bay in a container terminal so as to minimize the number of relocations. Unlike the offline version of the problem, the order of container retrievals is revealed one at a time in an online fashion. We analyze the so-called leveling heuristic using the perspective of worst-case competitive analysis of online algorithms and derive its competitive ratio. We then provide some computational experiments which give insights on the actual average performance of the heuristic.

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  • Zehendner, Elisabeth & Feillet, Dominique & Jaillet, Patrick, 2017. "An algorithm with performance guarantee for the Online Container Relocation Problem," European Journal of Operational Research, Elsevier, vol. 259(1), pages 48-62.
    • Handle: RePEc:eee:ejores:v:259:y:2017:i:1:p:48-62
    DOI: 10.1016/j.ejor.2016.09.011
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    References listed on IDEAS

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    1. Yu, Mingzhu & Qi, Xiangtong, 2013. "Storage space allocation models for inbound containers in an automatic container terminal," European Journal of Operational Research, Elsevier, vol. 226(1), pages 32-45.
    2. Petering, Matthew E.H. & Hussein, Mazen I., 2013. "A new mixed integer program and extended look-ahead heuristic algorithm for the block relocation problem," European Journal of Operational Research, Elsevier, vol. 231(1), pages 120-130.
    3. Lehnfeld, Jana & Knust, Sigrid, 2014. "Loading, unloading and premarshalling of stacks in storage areas: Survey and classification," European Journal of Operational Research, Elsevier, vol. 239(2), pages 297-312.
    4. Caserta, Marco & Schwarze, Silvia & Voß, Stefan, 2012. "A mathematical formulation and complexity considerations for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 219(1), pages 96-104.
    5. Bortfeldt, Andreas & Forster, Florian, 2012. "A tree search procedure for the container pre-marshalling problem," European Journal of Operational Research, Elsevier, vol. 217(3), pages 531-540.
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    7. Zhao, Wenjuan & Goodchild, Anne V., 2010. "The impact of truck arrival information on container terminal rehandling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 327-343, May.
    8. Zehendner, Elisabeth & Caserta, Marco & Feillet, Dominique & Schwarze, Silvia & Voß, Stefan, 2015. "An improved mathematical formulation for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 245(2), pages 415-422.
    9. Jang, Dong-Won & Kim, Se Won & Kim, Kap Hwan, 2013. "The optimization of mixed block stacking requiring relocations," International Journal of Production Economics, Elsevier, vol. 143(2), pages 256-262.
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    Citations

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    Cited by:

    1. Jin, Bo & Tanaka, Shunji, 2023. "An exact algorithm for the unrestricted container relocation problem with new lower bounds and dominance rules," European Journal of Operational Research, Elsevier, vol. 304(2), pages 494-514.
    2. 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.
    3. 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).
    4. Boschma, René & Mes, Martijn R.K. & de Vries, Leon R., 2023. "Approximate dynamic programming for container stacking," European Journal of Operational Research, Elsevier, vol. 310(1), pages 328-342.
    5. 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.
    6. V. Galle & V. H. Manshadi & S. Borjian Boroujeni & C. Barnhart & P. Jaillet, 2018. "The Stochastic Container Relocation Problem," Transportation Science, INFORMS, vol. 52(5), pages 1035-1058, October.
    7. Raka Jovanovic & Shunji Tanaka & Tatsushi Nishi & Stefan Voß, 2019. "A GRASP approach for solving the Blocks Relocation Problem with Stowage Plan," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 702-729, September.
    8. Jovanovic, Raka & Tuba, Milan & Voß, Stefan, 2019. "An efficient ant colony optimization algorithm for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 78-90.
    9. 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).
    10. Tanaka, Shunji & Tierney, Kevin, 2018. "Solving real-world sized container pre-marshalling problems with an iterative deepening branch-and-bound algorithm," European Journal of Operational Research, Elsevier, vol. 264(1), pages 165-180.
    11. 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.
    12. Facchini, F. & Digiesi, S. & Mossa, G., 2020. "Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making," International Journal of Production Economics, Elsevier, vol. 219(C), pages 164-178.
    13. Jin, Bo & Yu, Zhishan & Yu, Mingzhu, 2022. "Inbound container remarshaling problem in an automated container terminal," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

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