IDEAS home Printed from https://ideas.repec.org/a/pal/marecl/v24y2022i2d10.1057_s41278-021-00208-4.html
   My bibliography  Save this article

A constraint programming approach to capacity planning in container vessels

Author

Listed:
  • Byung Kwon Lee

    (National University of Singapore)

  • Joyce M. W. Low

    (Singapore Management University)

Abstract

A container vessel carries containers of various characteristics, in terms of size, weight, and contents. The cargo load of a container vessel, being subjected to a set of operational conditions and restrictions regarding ship stability and safety, is a fundamental element in decision-making when a shipping line provides logistics services to clients. This study presents a constraint programming-based model for the capacity planning of a container vessel under various operational conditions. The proposed model generates base solutions and is complemented with a rich scenario-based analysis that utilizes real-life ship data of a container vessel operated by a liner shipping company with a significant market presence. Solutions obtained from the model provide insights on containership capacity planning with differing settings and search strategies. Recommendations to container carriers, regarding improved capacity planning, are the highlights of the study.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:marecl:v:24:y:2022:i:2:d:10.1057_s41278-021-00208-4
    DOI: 10.1057/s41278-021-00208-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41278-021-00208-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41278-021-00208-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Olaf Merk, 2018. "Container Ship Size and Port Relocation," International Transport Forum Discussion Papers 2018/10, OECD Publishing.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Parreño, Francisco & Pacino, Dario & Alvarez-Valdes, Ramon, 2016. "A GRASP algorithm for the container stowage slot planning problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 141-157.
    8. Sciomachen, Anna & Tanfani, Elena, 2007. "A 3D-BPP approach for optimising stowage plans and terminal productivity," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1433-1446, December.
    9. 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.
    10. Rune Larsen & Dario Pacino, 2021. "A heuristic and a benchmark for the stowage planning problem," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 94-122, March.
    11. Shih-Liang Chao & Pi-Hung Lin, 2021. "Minimizing overstowage in master bay plans of large container ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 71-93, March.
    12. Imai, Akio & Sasaki, Kazuya & Nishimura, Etsuko & Papadimitriou, Stratos, 2006. "Multi-objective simultaneous stowage and load planning for a container ship with container rehandle in yard stacks," European Journal of Operational Research, Elsevier, vol. 171(2), pages 373-389, June.
    13. Mordecai Avriel & Michal Penn & Naomi Shpirer & Smadar Witteboon, 1998. "Stowage planning for container ships to reduce the number of shifts," Annals of Operations Research, Springer, vol. 76(0), pages 55-71, January.
    14. Iris, Çağatay & Christensen, Jonas & Pacino, Dario & Ropke, Stefan, 2018. "Flexible ship loading problem with transfer vehicle assignment and scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 113-134.
    15. Lee, Choong Bae & Wan, Junbin & Shi, Wenming & Li, Kevin, 2014. "A cross-country study of competitiveness of the shipping industry," Transport Policy, Elsevier, vol. 35(C), pages 366-376.
    16. I D Wilson & P A Roach, 2000. "Container stowage planning: a methodology for generating computerised solutions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(11), pages 1248-1255, November.
    17. 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.
    18. Shin-Chan Ting * & Gwo-Hshiung Tzeng, 2004. "An optimal containership slot allocation for liner shipping revenue management," Maritime Policy & Management, Taylor & Francis Journals, vol. 31(3), pages 199-211, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Fazi, Stefano, 2019. "A decision-support framework for the stowage of maritime containers in inland shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 1-23.
    3. Rune Larsen & Dario Pacino, 2021. "A heuristic and a benchmark for the stowage planning problem," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 94-122, March.
    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. 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.
    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. 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.
    8. Parreño, Francisco & Pacino, Dario & Alvarez-Valdes, Ramon, 2016. "A GRASP algorithm for the container stowage slot planning problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 141-157.
    9. Kong, Lingrui & Ji, Mingjun & Gao, Zhendi, 2021. "Joint optimization of container slot planning and truck scheduling for tandem quay cranes," European Journal of Operational Research, Elsevier, vol. 293(1), pages 149-166.
    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. 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.
    12. R. Roberti & D. Pacino, 2018. "A Decomposition Method for Finding Optimal Container Stowage Plans," Service Science, INFORMS, vol. 52(6), pages 1444-1462, December.
    13. Shih-Liang Chao & Pi-Hung Lin, 0. "Minimizing overstowage in master bay plans of large container ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 0, pages 1-23.
    14. Shih-Liang Chao & Pi-Hung Lin, 2021. "Minimizing overstowage in master bay plans of large container ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 71-93, March.
    15. 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.
    16. 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.
    17. 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.
    18. Jone R. Hansen & Kjetil Fagerholt & Magnus Stålhane & Jørgen G. Rakke, 2020. "An adaptive large neighborhood search heuristic for the planar storage location assignment problem: application to stowage planning for Roll-on Roll-off ships," Journal of Heuristics, Springer, vol. 26(6), pages 885-912, December.
    19. 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.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:marecl:v:24:y:2022:i:2:d:10.1057_s41278-021-00208-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.