IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-642-20009-0_53.html
   My bibliography  Save this book chapter

Stochastic Extensions to FlopC++

In: Operations Research Proceedings 2010

Author

Listed:
  • Christian Wolf

    (University of Paderborn)

  • Achim Koberstein

    (University of Paderborn)

  • Tim Hultberg

Abstract

We extend the open-source modelling language FlopC++, which is part of the COIN-OR project, to support multi-stage stochastic programs with recourse. We connect the stochastic version of FlopC++ to the existing COIN class stochastic modelling interface (SMI) to provide a direct interface to specialized solution algorithms. The new stochastic version of FlopC++ can be used to specify scenario-based problems and distribution-based problems with independent random variables. A data-driven scenario tree generation method transforms a given scenario fan, a collection of different data paths with specified probabilities, into a scenario tree. We illustrate our extensions by means of a two-stage mixed integer strategic supply chain design problem and a multi-stage investment model.

Suggested Citation

  • Christian Wolf & Achim Koberstein & Tim Hultberg, 2011. "Stochastic Extensions to FlopC++," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 333-338, Springer.
    • Handle: RePEc:spr:oprchp:978-3-642-20009-0_53
    DOI: 10.1007/978-3-642-20009-0_53
    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.

    Citations

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


    Cited by:

    1. Weskamp, Christoph & Koberstein, Achim & Schwartz, Frank & Suhl, Leena & Voß, Stefan, 2019. "A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand," Omega, Elsevier, vol. 83(C), pages 123-138.

    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:978-3-642-20009-0_53. 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.