IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v60y2022i3p957-976.html
   My bibliography  Save this article

A hybrid multiobjective GRASP for a multi-row facility layout problem with extra clearances

Author

Listed:
  • Xing Wan
  • Xingquan Zuo
  • Xiaodong Li
  • Xinchao Zhao

Abstract

The multi-row facility layout problem (MRLP) is an important design problem often encountered in real life. Existing studies on MRLPs typically either ignore clearances between adjacent machines or consider only the minimum clearances. However, separating adjacent machines with clearances greater than the minimum ones may achieve lower material flow cost. In addition, current studies on MRLPs ignore the optimisation of layout area. In this paper, we study a multi-row facility layout problem with extra clearances (MRLP-EC), with the objectives of minimising material flow cost and layout area. A mixed integer programming formulation is established for MRLP-EC. A hybrid approach combining an improved multi-objective greedy randomised adaptive search procedure (mGRASP) and linear programming (LP) is proposed for the problem. The mGRASP is used to optimise machine sequences to obtain a set of non-dominated machine sequences. A segments-based dominance method is suggested to measure the dominance relationship of any pair of machine sequences. LP is used to optimise extra clearances between adjacent machines (i.e. the exact location of each machine) for each non-dominated machine sequence. The proposed approach is compared against an exact method and two multi-objective heuristics. Experiments show that the approach is effective for MRLP-EC and outperforms comparative approaches.

Suggested Citation

  • Xing Wan & Xingquan Zuo & Xiaodong Li & Xinchao Zhao, 2022. "A hybrid multiobjective GRASP for a multi-row facility layout problem with extra clearances," International Journal of Production Research, Taylor & Francis Journals, vol. 60(3), pages 957-976, February.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:3:p:957-976
    DOI: 10.1080/00207543.2020.1847342
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2020.1847342
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2020.1847342?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.

    Citations

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


    Cited by:

    1. Raka Jovanovic & Antonio P. Sanfilippo & Stefan Voß, 2022. "Fixed set search applied to the multi-objective minimum weighted vertex cover problem," Journal of Heuristics, Springer, vol. 28(4), pages 481-508, August.

    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:60:y:2022:i:3:p:957-976. 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.