IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v56y2022i6p1658-1676.html
   My bibliography  Save this article

Analysis and Design of Rack-Climbing Robotic Storage and Retrieval Systems

Author

Listed:
  • Wanying Chen

    (School of Management and e-Business, Zhejiang Gongshang University, Hangzhou 30018, China)

  • René De Koster

    (Rotterdam School of Management, Erasmus University, 3062PA Rotterdam, Netherlands)

  • Yeming Gong

    (Emlyon Business School, 69130 Ecully, France)

Abstract

Warehouses are becoming increasingly robotized. Autonomous rack-climbing robots have recently been introduced in e-commerce fulfillment centers. The robots not only retrieve loads from any level in a rack but also, roam the warehouse and bring the loads to order picking stations without using conveyors or lifts. This paper models and analyzes this system under both single and dual commands with different robot assignment (dedicated versus shared) and storage location assignment (class-based and random) policies. We study these policies in the presence of robot congestion. We evaluate the impact of two blocking protocols, a wait-outside-aisle policy and a block-and-recirculate policy, on the order throughput time. The system is modeled using semiopen queuing networks (SOQNs) for the different operating policies. The analytical models are validated using simulation. We also use this model to compare this system with a shuttle-based system. The results show that (1) the choice of the wait-outside-aisle policy or the block-and-recirculate policy mainly depends on the number of the robots in the system and the throughput requirement and that (2) the dedicated robot assignment policy can be an attractive policy, especially for a large system.

Suggested Citation

  • Wanying Chen & René De Koster & Yeming Gong, 2022. "Analysis and Design of Rack-Climbing Robotic Storage and Retrieval Systems," Transportation Science, INFORMS, vol. 56(6), pages 1658-1676, November.
  • Handle: RePEc:inm:ortrsc:v:56:y:2022:i:6:p:1658-1676
    DOI: 10.1287/trsc.2022.1140
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.2022.1140
    Download Restriction: no

    File URL: https://libkey.io/10.1287/trsc.2022.1140?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
    ---><---

    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:inm:ortrsc:v:56:y:2022:i:6:p:1658-1676. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.