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A new three-step heuristic for the Master Bay Plan Problem

Author

Listed:
  • Daniela Ambrosino

    (Department of Economics and Quantitative Methods (DiEM), University of Genova, Genova, Italy)

  • Davide Anghinolfi

    (Department of Communications, Computer and System Sciences (DIST), University of Genova, Genova, Italy)

  • Massimo Paolucci

    (Department of Communications, Computer and System Sciences (DIST), University of Genova, Genova, Italy)

  • Anna Sciomachen

    (Department of Economics and Quantitative Methods (DiEM), University of Genova, Genova, Italy)

Abstract

In this work, we are looking at the problem of determining stowage plans for containerships. This problem, denoted in the literature as the Master Bay Plan Problem (MBPP), is computationally difficult to solve, that is NP-hard. We start from the optimal solution of subsets of bays related to independent portions of the ship, which are determined by a previously proposed decomposition approach for the MBPP; then, we look for the global ship stability of the overall stowage plan by using a tabu search (TS) meta-heuristic approach. Note that at the same time the proposed TS algorithm allows us to further reduce the handling time of the containers to be loaded on the ship. The proposed heuristics has been implemented within a software support system that helps the planning management in the visualisation of the stowage plans of each bay of the ship. Preliminary computational experimentations performed on some real-life test cases related to a terminal located at the port of Genoa, Italy are provided. Maritime Economics & Logistics (2009) 11, 98–120. doi:10.1057/mel.2008.19

Suggested Citation

  • Daniela Ambrosino & Davide Anghinolfi & Massimo Paolucci & Anna Sciomachen, 2009. "A new three-step heuristic for the Master Bay Plan Problem," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 11(1), pages 98-120, March.
    • Handle: RePEc:pal:marecl:v:11:y:2009:i:1:p:98-120
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    Cited by:

    1. Daniela Ambrosino & Anna Sciomachen, 2021. "A shipping line stowage-planning procedure in the presence of hazardous containers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 49-70, March.
    2. R. Roberti & D. Pacino, 2018. "A Decomposition Method for Finding Optimal Container Stowage Plans," Service Science, INFORMS, vol. 52(6), pages 1444-1462, December.
    3. Christensen, Jonas & Erera, Alan & Pacino, Dario, 2019. "A rolling horizon heuristic for the stochastic cargo mix problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 200-220.
    4. Dalia Rashed & Amr Eltawil & Mohamed Gheith, 2021. "A Fuzzy Logic-Based Algorithm to Solve the Slot Planning Problem in Container Vessels," Logistics, MDPI, vol. 5(4), pages 1-24, September.
    5. Byung Kwon Lee & Joyce M. W. Low, 2022. "A constraint programming approach to capacity planning in container vessels," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 415-438, June.
    6. Monaco, Maria Flavia & Sammarra, Marcello & Sorrentino, Gregorio, 2014. "The Terminal-Oriented Ship Stowage Planning Problem," European Journal of Operational Research, Elsevier, vol. 239(1), pages 256-265.
    7. Christensen, Jonas & Pacino, Dario, 2017. "A matheuristic for the Cargo Mix Problem with Block Stowage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 151-171.
    8. Delgado, Alberto & Jensen, Rune Møller & Janstrup, Kira & Rose, Trine Høyer & Andersen, Kent Høj, 2012. "A Constraint Programming model for fast optimal stowage of container vessel bays," European Journal of Operational Research, Elsevier, vol. 220(1), pages 251-261.
    9. Chien-Chang Chou & Pao-Yi Fang, 2021. "Applying expert knowledge to containership stowage planning: an empirical study," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 4-27, March.
    10. Ding, Ding & Chou, Mabel C., 2015. "Stowage planning for container ships: A heuristic algorithm to reduce the number of shifts," European Journal of Operational Research, Elsevier, vol. 246(1), pages 242-249.
    11. Korach, Aleksandra & Brouer, Berit Dangaard & Jensen, Rune Møller, 2020. "Matheuristics for slot planning of container vessel bays," European Journal of Operational Research, Elsevier, vol. 282(3), pages 873-885.
    12. 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.

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