IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-319-00795-3_16.html
   My bibliography  Save this book chapter

A Genetic Algorithm for the Unequal Area Facility Layout Problem

In: Operations Research Proceedings 2012

Author

Listed:
  • Udo Buscher

    (TU Dresden)

  • Birgit Mayer

    (TU Dresden)

  • Tobias Ehrig

    (TU Dresden)

Abstract

In this paper we apply a genetic algorithm for solving the facility layout problem. The focus is on departments of unequal sizes. The objective is primarily to minimize material flow factor cost. The chosen genetic method bases on an implemented space-filling curve which continuously connects each unequal area department in order to avoid disjoint areas. In contrast to the existing literature, which applies sweeping, spiral or Hilbert-type patterns, we propose Peano-type patterns. The original Peano curve has to be adjusted in order to be applicable to the considered facility layout problem. We describe the generation of the Peano curve and the applied genetic search. Further, we provide results from several test problems that demonstrate the very good suitability of modified Peano curves for the unequal area facility layout problem.

Suggested Citation

  • Udo Buscher & Birgit Mayer & Tobias Ehrig, 2014. "A Genetic Algorithm for the Unequal Area Facility Layout Problem," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 109-114, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-00795-3_16
    DOI: 10.1007/978-3-319-00795-3_16
    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:978-3-319-00795-3_16. 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.