IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-030-48439-2_23.html
   My bibliography  Save this book chapter

Modeling of a Rich Bin Packing Problem from Industry

In: Operations Research Proceedings 2019

Author

Listed:
  • Nils-Hassan Quttineh

    (Linköping University)

Abstract

We present and share the experience of modeling a real-life optimization problem. This exercise in modeling is a text book example of how a naive, straightforward mixed-integer modeling approach leads to a highly intractable model, while a deeper problem analysis leads to a non-standard, much stronger model. Our development process went from a weak model with burdensome run times, via meta-heuristics and column generation, to end up with a strong model which solves the problem within seconds. The problem in question deals with the challenges of planning the order-driven continuous casting production at the Swedish steel producer SSAB. We study the cast planning problem, where the objective is to minimize production waste which unavoidably occurs as orders of different steel grades are cast in sequence. This application can be categorised as a rich bin packing problem.

Suggested Citation

  • Nils-Hassan Quttineh, 2020. "Modeling of a Rich Bin Packing Problem from Industry," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 191-197, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_23
    DOI: 10.1007/978-3-030-48439-2_23
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:oprchp:978-3-030-48439-2_23. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.