IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v53y2015i9p2674-2689.html
   My bibliography  Save this article

Heuristics for integrated job assignment and scheduling in the multi-plant remanufacturing system

Author

Listed:
  • Danping Lin
  • Chee Chong Teo
  • Carman Ka Man Lee

Abstract

We consider a multi-plant remanufacturing system where decisions have to be made on the choice of plant to perform the remanufacturing and the remanufacturing options. Each plant is in different geographical locations and differs in technological capability, labour cost, distance from customers, taxes and duties. There are three options of remanufacture: replacement, repair and recondition. Furthermore, the probability that each remanufacture job needs to be reworked depends on the remanufacturing option selected. We show the interdependencies among the plant selection, remanufacturing option and job scheduling when subject to resource constraints, which motivate the integrated solution proposed in this paper. The solution method is composed of the linear physical programming and the multi-level encoding genetic algorithm (GA). By performing a case study, we illustrate the use of the model and we present the resulting managerial insights. The results show that the proposed integrated approach performs better compared with the regular GA in terms of makespan.

Suggested Citation

  • Danping Lin & Chee Chong Teo & Carman Ka Man Lee, 2015. "Heuristics for integrated job assignment and scheduling in the multi-plant remanufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 53(9), pages 2674-2689, May.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:9:p:2674-2689
    DOI: 10.1080/00207543.2014.975851
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2014.975851
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2014.975851?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. Yaping Ren & Xinyu Lu & Hongfei Guo & Zhaokang Xie & Haoyang Zhang & Chaoyong Zhang, 2023. "A Review of Combinatorial Optimization Problems in Reverse Logistics and Remanufacturing for End-of-Life Products," Mathematics, MDPI, vol. 11(2), pages 1-24, January.

    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:53:y:2015:i:9:p:2674-2689. 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.