IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v62y2024i23p8373-8396.html
   My bibliography  Save this article

Many-to-many locomotive routing problem for the steel industry

Author

Listed:
  • Ohhyun Kweon
  • Byung-In Kim

Abstract

The locomotive routing problem (LRP) considers the transportation of non-motorised containers called torpedo ladle cars (TPCs) within a steelworks. Locomotives are responsible for picking up and delivering TPCs to fulfil requests for various facilities, including steelmaking, ironmaking, heating, and repair facilities. This study introduces the many-to-many locomotive routing problem (M2MLRP), specifically tailored for the steel industry. M2MLRP was formulated using pattern- and routing-based models, and a logic-based Benders-decomposition-based matheuristic algorithm was developed. The pattern-based model successfully solved 20 small randomly generated instances, while the proposed matheuristic algorithm demonstrated the rapid generation of near-optimal solutions. Notably, unlike the pattern- and routing-based models, the proposed algorithm extended its capability to generate good feasible solutions for medium- and large-sized instances. Across all instances, the matheuristic algorithm outperformed both the routing-based model and an adaptive large neighbourhood search algorithm, showcasing its superior solution quality. This study provides a significant contribution to the field by being the first to address M2MLRP in the context of the steel industry.

Suggested Citation

  • Ohhyun Kweon & Byung-In Kim, 2024. "Many-to-many locomotive routing problem for the steel industry," International Journal of Production Research, Taylor & Francis Journals, vol. 62(23), pages 8373-8396, December.
  • Handle: RePEc:taf:tprsxx:v:62:y:2024:i:23:p:8373-8396
    DOI: 10.1080/00207543.2024.2342017
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2024.2342017
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2024.2342017?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:62:y:2024:i:23:p:8373-8396. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.