IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v59y2021i9p2739-2771.html
   My bibliography  Save this article

Accelerating mathematical programming techniques with the corridor method

Author

Listed:
  • Marco Caserta
  • Stefan Voß

Abstract

In this paper we investigate how the Benders decomposition, Lagrangean relaxation, and Dantzig–Wolfe reformulation techniques can be accelerated when intertwined with the corridor method. We test the approaches on the capacitated lot sizing problem with setups. Due to the computational complexity of this lot sizing problem, one would expect to find a number of approaches based on decomposition techniques in the literature. While this is true for Lagrangean relaxation and Dantzig–Wolfe reformulation, we could not find any paper proposing the use of Benders decomposition for the problem at hand. Consequently, with this study, we pursue a two-fold goal: First, and foremost, we want to determine how effective the corridor method is as acceleration scheme for these decomposition techniques; second, we aim at gaining some insight into why Benders has not been proposed for this class of problems. Our results shed light on both issues. On the one hand, we show that all the decomposition methods benefit from the hybridisation with the corridor method. On the other hand, a thorough analysis on the behaviour and limitations of Benders algorithm is provided. We conclude the study with a statistical analysis to determine whether significant differences in performance among the different implementations arise.

Suggested Citation

  • Marco Caserta & Stefan Voß, 2021. "Accelerating mathematical programming techniques with the corridor method," International Journal of Production Research, Taylor & Francis Journals, vol. 59(9), pages 2739-2771, May.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:9:p:2739-2771
    DOI: 10.1080/00207543.2020.1740343
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2020.1740343
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2020.1740343?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:59:y:2021:i:9:p:2739-2771. 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.