IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v51y2019i9p957-971.html
   My bibliography  Save this article

Space-efficient layouts for block stacking warehouses

Author

Listed:
  • Shahab Derhami
  • Jeffrey S. Smith
  • Kevin R. Gue

Abstract

In block stacking warehouses, pallets of Stock Keeping Units (SKUs) are stacked on top of one another in lanes on the warehouse floor. A conventional layout consists of multiple bays of lanes separated by aisles. The depths of the bays and the number of aisles determine the storage space utilization. Using an analytical model, we show that the traditional lane depth model underestimates accessibility waste and therefore does not provide an optimal lane depth. We propose a new model of wasted storage space and embed it in a mixed-integer program to find the optimal bay depths. The model improves space utilization by allowing multiple bay depths and allocating SKUs to appropriate bays. Our computational study shows the proposed model is capable of solving large-scale problems with a relatively small optimality gap. We use simulation to evaluate performance of the proposed model on small to industrial-sized warehouses. We also include a case study from the beverage industry.

Suggested Citation

  • Shahab Derhami & Jeffrey S. Smith & Kevin R. Gue, 2019. "Space-efficient layouts for block stacking warehouses," IISE Transactions, Taylor & Francis Journals, vol. 51(9), pages 957-971, September.
  • Handle: RePEc:taf:uiiexx:v:51:y:2019:i:9:p:957-971
    DOI: 10.1080/24725854.2018.1539280
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24725854.2018.1539280
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/24725854.2018.1539280?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. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.
    2. Derhami, Shahab & Smith, Jeffrey S. & Gue, Kevin R., 2020. "A simulation-based optimization approach to design optimal layouts for block stacking warehouses," International Journal of Production Economics, Elsevier, vol. 223(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:taf:uiiexx:v:51:y:2019:i:9:p:957-971. 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/uiie .

    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.