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A mathematical formulation and efficient heuristics for the dynamic container relocation problem

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  • M. Hakan Akyüz
  • Chung‐Yee Lee

Abstract

The container relocation problem (CRP) is concerned with emptying a single yard‐bay which contains J containers each following a given pickup order so as to minimize the total number of relocations made during their retrieval process. The CRP can be modeled as a binary integer programming (IP) problem and is known to be NP‐hard. In this work, we focus on an extension of the CRP to the case where containers are both received and retrieved from a single yard‐bay, and call it the dynamic container relocation problem. The arrival (departure) sequences of containers to (from) the yard‐bay is assumed to be known a priori. A binary IP formulation is presented for the problem. Then, we propose three types of heuristic methods: index based heuristics, heuristics using the binary IP formulation, and a beam search heuristic. Computational experiments are performed on an extensive set of randomly generated test instances. Our results show that beam search heuristic is very efficient and performs better than the other heuristic methods.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 101–118, 2014

Suggested Citation

  • M. Hakan Akyüz & Chung‐Yee Lee, 2014. "A mathematical formulation and efficient heuristics for the dynamic container relocation problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(2), pages 101-118, March.
    • Handle: RePEc:wly:navres:v:61:y:2014:i:2:p:101-118
    DOI: 10.1002/nav.21569
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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. 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.
    3. 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.
    4. 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.
    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.
    6. Kap Hwan Kim & Sanghyuk Yi, 2021. "Utilizing information sources to reduce relocation of inbound containers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(4), pages 726-749, December.
    7. Juan P. Cavada & Cristián E. Cortés & Pablo A. Rey, 2023. "Comparing allocation and relocation policies at a logistics service container terminal: a discrete-event simulation approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1281-1316, December.
    8. Ruiyou Zhang & Shixin Liu & Herbert Kopfer, 2016. "Tree search procedures for the blocks relocation problem with batch moves," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 397-424, September.
    9. 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.
    10. 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).
    11. Huiling Zhu & Mingjun Ji & Wenwen Guo & Qingbin Wang & Yongzhi Yang, 2019. "Mathematical formulation and heuristic algorithm for the block relocation and loading problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(4), pages 333-351, June.

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