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Integer programming models for the pre-marshalling problem

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  • Parreño-Torres, Consuelo
  • Alvarez-Valdes, Ramon
  • Ruiz, Rubén

Abstract

The performance of shipping companies greatly depends on reduced berthing times. The trend towards bigger ships and shorter berthing times places severe stress on container terminals, which cannot simply increase the available cranes indefinitely. Therefore, the focus is on optimizing existing resources. An effective way of speeding up the loading/unloading operations of ships at the container terminal is to use the idle time before the arrival of a ship for sorting the stored containers in advance. The pre-marshalling problem consists in rearranging the containers placed in a bay in the order in which they will be required later, looking for a sequence with the minimum number of moves. With sorted bays, loading/unloading operations are significantly faster, as there is no longer a need to make unproductive moves in the bays once ships are berthed. In this paper, we address the pre-marshalling problem by developing and testing integer linear programming models. Two alternative families of models are proposed, as well as an iterative solution procedure that does not depend on a difficult to obtain upper bound. An extensive computational analysis has been carried out over several well-known datasets from the literature. This analysis has allowed us to test the performance of the models, and to conclude that the performance of the best proposed model is superior to that of previously published alternatives.

Suggested Citation

  • Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Ruiz, Rubén, 2019. "Integer programming models for the pre-marshalling problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 142-154.
  • Handle: RePEc:eee:ejores:v:274:y:2019:i:1:p:142-154
    DOI: 10.1016/j.ejor.2018.09.048
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    References listed on IDEAS

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    1. de Melo da Silva, Marcos & Toulouse, Sophie & Wolfler Calvo, Roberto, 2018. "A new effective unified model for solving the Pre-marshalling and Block Relocation Problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 40-56.
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    3. 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.
    4. 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.
    5. 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.
    6. Robert E. Bixby, 2002. "Solving Real-World Linear Programs: A Decade and More of Progress," Operations Research, INFORMS, vol. 50(1), pages 3-15, February.
    7. Lee, Yusin & Chao, Shih-Liang, 2009. "A neighborhood search heuristic for pre-marshalling export containers," European Journal of Operational Research, Elsevier, vol. 196(2), pages 468-475, July.
    8. Raka Jovanovic & Milan Tuba & Stefan Voß, 2017. "A multi-heuristic approach for solving the pre-marshalling problem," 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. 25(1), pages 1-28, March.
    9. 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.
    10. 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.
    11. Wang, Ning & Jin, Bo & Lim, Andrew, 2015. "Target-guided algorithms for the container pre-marshalling problem," Omega, Elsevier, vol. 53(C), pages 67-77.
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    Cited by:

    1. Boge, Sven & Goerigk, Marc & Knust, Sigrid, 2020. "Robust optimization for premarshalling with uncertain priority classes," European Journal of Operational Research, Elsevier, vol. 287(1), pages 191-210.
    2. 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.
    3. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    4. Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Ruiz, Rubén & Tierney, Kevin, 2020. "Minimizing crane times in pre-marshalling problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    5. Maniezzo, Vittorio & Boschetti, Marco A. & Gutjahr, Walter J., 2021. "Stochastic premarshalling of block stacking warehouses," Omega, Elsevier, vol. 102(C).
    6. Jiménez-Piqueras, Celia & Ruiz, Rubén & Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon, 2023. "A constraint programming approach for the premarshalling problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 668-678.
    7. 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.
    8. Ignacio Araya & Martín Toledo, 2023. "A fill-and-reduce greedy algorithm for the container pre-marshalling problem," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    9. Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Parreño, Francisco, 2022. "A beam search algorithm for minimizing crane times in premarshalling problems," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1063-1078.
    10. Tanaka, Shunji & Tierney, Kevin & Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Ruiz, Rubén, 2019. "A branch and bound approach for large pre-marshalling problems," European Journal of Operational Research, Elsevier, vol. 278(1), pages 211-225.
    11. Ebenezer Fiifi Emire Atta Mills & Bo Yu & Kailin Zeng, 2019. "Satisfying Bank Capital Requirements: A Robustness Approach in a Modified Roy Safety-First Framework," Mathematics, MDPI, vol. 7(7), pages 1-20, July.
    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. 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.
    14. Pfrommer, Jakob & Meyer, Anne & Tierney, Kevin, 2024. "Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1054-1071.
    15. Zhang, Canrong & Wang, Qi & Yuan, Guoping, 2023. "Novel models and algorithms for location assignment for outbound containers in container terminals," European Journal of Operational Research, Elsevier, vol. 308(2), pages 722-737.

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