IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v57y2019i10p3003-3019.html
   My bibliography  Save this article

Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system

Author

Listed:
  • Chen Chen
  • Lee Kong Tiong
  • I-Ming Chen

Abstract

In this article, scheduling problem of a space-constrained AGV-based prefabricated bathroom units (PBU) manufacturing system is addressed. Space becomes a key resource to this manufacturing system because a very large space is required to accommodate the settling units as well as the queues. Although line balancing helps to reduce the queues, the system is still prone to deadlock due to limited space. Hence, in order to prevent deadlock situations, the production start times of PBUs have to be controlled. A genetic algorithm is proposed with the objective to decide operation for each workstation and to choose a start time for each PBU. The project duration is minimised while satisfying precedence relations and resource availabilities. A rule-based simulation approach is used to estimate the fitness value of every GA chromosomes. At last, the experiment based on data from an industrial project shows that the proposed algorithm has the potential to guide the real practice.

Suggested Citation

  • Chen Chen & Lee Kong Tiong & I-Ming Chen, 2019. "Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 3003-3019, May.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3003-3019
    DOI: 10.1080/00207543.2018.1521532
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1521532
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2018.1521532?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:57:y:2019:i:10:p:3003-3019. 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.