IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/2939272.html
   My bibliography  Save this article

Scheduling Just-in-Time Transport Vehicles to Feed Parts for Mixed Model Assembly Lines

Author

Listed:
  • Yunfang Peng
  • Tian Zeng
  • Yajuan Han
  • Beixin Xia

Abstract

In order to solve the problem of vehicle scheduling to feed parts at automobile assembly line, this study proposes a just-in-time delivery method combined with the mode of material supermarket. A mixed integer linear programming model with the primary objective of using the least number of tow trains is constructed by considering capacity of vehicle and inventory levels of line. On the basis of the minimum number of tow trains, the schedule of each tour is reasonably planned to minimize inventory of assembly line, which is the secondary objective of the part supply problem. Additionally, a heuristic algorithm which can obtain a satisfactory solution in a short time is designed to solve large-scale problems after considering continuity and complexity of modern automobile production. Furthermore, some cases are analyzed and compared with the widely used periodic delivery strategy, and the feasibility of just-in-time model and algorithm is verified. The results reveal that just-in-time delivery strategy has more advantages in reducing inventory level than periodic delivery strategy.

Suggested Citation

  • Yunfang Peng & Tian Zeng & Yajuan Han & Beixin Xia, 2020. "Scheduling Just-in-Time Transport Vehicles to Feed Parts for Mixed Model Assembly Lines," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-13, April.
  • Handle: RePEc:hin:jnddns:2939272
    DOI: 10.1155/2020/2939272
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2020/2939272.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/DDNS/2020/2939272.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/2939272?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
    ---><---

    Citations

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


    Cited by:

    1. Bingtao Quan & Sujian Li & Kuo-Jui Wu, 2022. "Optimizing the Vehicle Scheduling Problem for Just-in-Time Delivery Considering Carbon Emissions and Atmospheric Particulate Matter," Sustainability, MDPI, vol. 14(10), pages 1-19, May.

    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:hin:jnddns:2939272. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.