IDEAS home Printed from https://ideas.repec.org/a/hin/complx/4595316.html
   My bibliography  Save this article

A Polling-Based Dynamic Order-Picking System considering Priority Orders

Author

Listed:
  • Wenxue Ran
  • Sen Liu
  • Zhe Zhang

Abstract

Nowadays, how to offer extremely fast response to customer orders has become a major challenge for warehouse management, especially in e-commerce. Due to the time urgency aspect of some “VIP” orders that need priority processing, one of the most important issues for logistics distribution centres is how to improve the VIP order-picking priority without reducing the common order-picking efficiency. With this consideration, this article put forward a new priority polling model to describe and analyse this problem. We divide orders into priority and common categories according to their time urgency. A mathematical model is established for such a system by applying polling theory, a probability generating function, and an embedded Markov chain. Numerical analysis shows that this priority polling-based picking system can improve the picking efficiency and is well suited to practical operations.

Suggested Citation

  • Wenxue Ran & Sen Liu & Zhe Zhang, 2020. "A Polling-Based Dynamic Order-Picking System considering Priority Orders," Complexity, Hindawi, vol. 2020, pages 1-15, July.
  • Handle: RePEc:hin:complx:4595316
    DOI: 10.1155/2020/4595316
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2020/4595316.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2020/4595316.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/4595316?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. Chen, Chengcheng & Wang, Xianchang & Yu, Helong & Wang, Mingjing & Chen, Huiling, 2021. "Dealing with multi-modality using synthesis of Moth-flame optimizer with sine cosine mechanisms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 291-318.
    2. Yu, Hongxin & Zhao, Yuanjun & Liu, Zheng & Liu, Wei & Zhang, Shuai & Wang, Fatao & Shi, Lihua, 2021. "Research on the financing income of supply chains based on an E-commerce platform," Technological Forecasting and Social Change, Elsevier, vol. 169(C).

    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:complx:4595316. 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.