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A beam search algorithm for minimizing crane times in premarshalling problems

Author

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  • Parreño-Torres, Consuelo
  • Alvarez-Valdes, Ramon
  • Parreño, Francisco

Abstract

The premarshalling problem consists of sorting the containers placed in a bay of the container yard so that they can be retrieved in the order in which they will be required. We study the premarshalling problem with crane time minimization objective and develop a beam search algorithm, with some new elements adapted to the characteristics of the problem, to solve it. We propose various evaluation criteria, depending on the type of container movement, for its local evaluation; a new heuristic algorithm including local search for blue its global evaluation; and several new dominance rules. The computational study shows the contribution of each new element. The performance of the complete algorithm is tested on well-known benchmarks. The beam search algorithm matches all known optimal solutions, improves on the known suboptimal solutions, and obtains solutions for the largest instances, for which no solution had previously been found.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:302:y:2022:i:3:p:1063-1078
    DOI: 10.1016/j.ejor.2022.01.038
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Kevin Tierney & Dario Pacino & Stefan Voß, 2017. "Solving the pre-marshalling problem to optimality with A* and IDA," Flexible Services and Manufacturing Journal, Springer, vol. 29(2), pages 223-259, June.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Wang, Ning & Jin, Bo & Lim, Andrew, 2015. "Target-guided algorithms for the container pre-marshalling problem," Omega, Elsevier, vol. 53(C), pages 67-77.
    9. 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).
    10. 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.
    11. 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.
    12. Wang, Ning & Jin, Bo & Zhang, Zizhen & Lim, Andrew, 2017. "A feasibility-based heuristic for the container pre-marshalling problem," European Journal of Operational Research, Elsevier, vol. 256(1), pages 90-101.
    13. Maniezzo, Vittorio & Boschetti, Marco A. & Gutjahr, Walter J., 2021. "Stochastic premarshalling of block stacking warehouses," Omega, Elsevier, vol. 102(C).
    14. Parreño, F. & Alonso, M.T. & Alvarez-Valdes, R., 2020. "Solving a large cutting problem in the glass manufacturing industry," European Journal of Operational Research, Elsevier, vol. 287(1), pages 378-388.
    15. Peixin Ge & Ying Meng & Jiyin Liu & Lixin Tang & Ren Zhao, 2020. "Logistics optimisation of slab pre-marshalling problem in steel industry," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4050-4070, July.
    16. 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.
    17. Libralesso, Luc & Fontan, Florian, 2021. "An anytime tree search algorithm for the 2018 ROADEF/EURO challenge glass cutting problem," European Journal of Operational Research, Elsevier, vol. 291(3), pages 883-893.
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