IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v58y2020i22p6970-6984.html
   My bibliography  Save this article

Simulation-based solution for a dynamic multi-crane-scheduling problem in a steelmaking shop

Author

Listed:
  • Ji Li
  • Anjun Xu
  • Xuesong Zang

Abstract

Here, we present a simulation-based solution for a multi-crane-scheduling problem derived from a steelmaking shop. This problem features non-conflict constraint between cranes, station-capacity constraint, and jobs with inaccurate release times and different temporal scheduling objectives. The predictive–reactive rescheduling strategy was applied to solve the problem. The problem was modelled considering different temporal objectives for the jobs and workload objective for the cranes and the model was solved by a heuristic. In the simulation, the jobs were not directly given but generated by a job-prediction method. The cranes’ moving behaviours were controlled by a designed crane trajectory solution. Experimental tests were conducted using data from the site and the results show that the proposed crane-scheduling solution provided better scheduling results than both the exhaustive method and the method that is used in the production field. The best predictive spans for the jobs in this specific crane-scheduling problem were found to be 7–14 min. The real-time performance of the crane-scheduling solution is demonstrated to highly guarantee its practicability.

Suggested Citation

  • Ji Li & Anjun Xu & Xuesong Zang, 2020. "Simulation-based solution for a dynamic multi-crane-scheduling problem in a steelmaking shop," International Journal of Production Research, Taylor & Francis Journals, vol. 58(22), pages 6970-6984, November.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:22:p:6970-6984
    DOI: 10.1080/00207543.2019.1687952
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2019.1687952
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2019.1687952?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:58:y:2020:i:22:p:6970-6984. 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.