IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v50y2025i3p392-412.html
   My bibliography  Save this article

A comprehensive approach to UA facility layout design using genetic algorithm

Author

Listed:
  • Kamal Deep

Abstract

Facility layout planning is a quantum leap for the production industry to realise the low entropy, widely applied to the unequal area facility layout problems (UA-FLPs). This paper aims at the optimisation of UA-facility layout in the flexible bays structure (FBS) to maximise the adjacency requirements of facility types for the production layout. The FBS is a most commonly used structure flexible to allocate the facilities in the bays of unequal areas permitting empty space in the total area of the layout. The proposed mixed integer programming model has been formulated to ensure; minimum side length, confined aspect ratio of facility types, and optimal space utilisation in the total area of facility layout. The genetic algorithm based heuristic has been used to search the discrete solution space in a feasible time span. The optimal results obtained are mapped with the best-known numerical instances reported in the literature to approve the efficacy of proposed solution approach.

Suggested Citation

  • Kamal Deep, 2025. "A comprehensive approach to UA facility layout design using genetic algorithm," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 50(3), pages 392-412.
  • Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:392-412
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=147681
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:ids:ijisen:v:50:y:2025:i:3:p:392-412. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=188 .

    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.