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Research into container reshuffling and stacking problems in container terminal yards

Author

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  • Lixin Tang
  • Wei Jiang
  • Jiyin Liu
  • Yun Dong

Abstract

Container stacking and reshuffling are important issues in the management of operations in a container terminal. Minimizing the number of reshuffles can increase productivity of the yard cranes and the efficiency of the terminal. In this research, the authors improve the existing static reshuffling model, develop five effective heuristics, and analyze the performance of these algorithms. A discrete-event simulation model is developed to animate the stacking, retrieving, and reshuffling operations and to test the performance of the proposed heuristics and their extended versions in a dynamic environment with arrivals and retrievals of containers. The experimental results for the static problem show that the improved model can solve the reshuffling problem more quickly than the existing model and the proposed extended heuristics are superior to the existing ones. The experimental results for the dynamic problem show that the results of the extended versions of the five proposed heuristics are superior or similar to the best results of the existing heuristics and consume very little time.

Suggested Citation

  • Lixin Tang & Wei Jiang & Jiyin Liu & Yun Dong, 2015. "Research into container reshuffling and stacking problems in container terminal yards," IISE Transactions, Taylor & Francis Journals, vol. 47(7), pages 751-766, July.
    • Handle: RePEc:taf:uiiexx:v:47:y:2015:i:7:p:751-766
    DOI: 10.1080/0740817X.2014.971201
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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. Ting, Ching-Jung & Wu, Kun-Chih, 2017. "Optimizing container relocation operations at container yards with beam search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 17-31.
    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. 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.
    6. Sun, Defeng & Meng, Ying & Tang, Lixin & Liu, Jinyin & Huang, Baobin & Yang, Jiefu, 2020. "Storage space allocation problem at inland bulk material stockyard," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    7. Lixin Tang & Jiyin Liu & Fei Yang & Feng Li & Kun Li, 2015. "Modeling and solution for the ship stowage planning problem of coils in the steel industry," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(7), pages 564-581, October.
    8. Yuan, Yuan & Tang, Lixin, 2017. "Novel time-space network flow formulation and approximate dynamic programming approach for the crane scheduling in a coil warehouse," European Journal of Operational Research, Elsevier, vol. 262(2), pages 424-437.
    9. Zhou, Chenhao & Wang, Wencheng & Li, Haobin, 2020. "Container reshuffling considered space allocation problem in container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    10. Bacci, Tiziano & Mattia, Sara & Ventura, Paolo, 2020. "A branch-and-cut algorithm for the restricted Block Relocation Problem," European Journal of Operational Research, Elsevier, vol. 287(2), pages 452-459.
    11. Sun, Defeng & Tang, Lixin & Baldacci, Roberto, 2019. "A Benders decomposition-based framework for solving quay crane scheduling problems," European Journal of Operational Research, Elsevier, vol. 273(2), pages 504-515.
    12. 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.
    13. 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.
    14. 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).
    15. Sun, Defeng & Tang, Lixin & Baldacci, Roberto & Lim, Andrew, 2021. "An exact algorithm for the unidirectional quay crane scheduling problem with vessel stability," European Journal of Operational Research, Elsevier, vol. 291(1), pages 271-283.

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