IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v43y2011i10p703-720.html
   My bibliography  Save this article

Turnover-based storage in non-traditional unit-load warehouse designs

Author

Listed:
  • Letitia Pohl
  • Russell Meller
  • Kevin Gue

Abstract

This article investigates the effect of assigning the most-active items to the best locations in unit-load warehouses with non-traditional aisles. Specifically, the performance of flying-V and fishbone designs are investigated when products exhibit different velocity profiles. Both single- and dual-command operations are considered for a warehouse where receiving and shipping are located at the midpoint of one side of the warehouse. For dual-command operations, a fishbone design shows similar reductions in travel distances for both random and turnover-based storage policies. The fishbone designs that provide the best performance have a diagonal cross aisle that extends to the upper corners of the picking space and are approximately half as tall as they are wide. In general, warehouse design parameters that perform best under random storage also perform well under turnover-based storage.

Suggested Citation

  • Letitia Pohl & Russell Meller & Kevin Gue, 2011. "Turnover-based storage in non-traditional unit-load warehouse designs," IISE Transactions, Taylor & Francis Journals, vol. 43(10), pages 703-720.
  • Handle: RePEc:taf:uiiexx:v:43:y:2011:i:10:p:703-720
    DOI: 10.1080/0740817X.2010.549098
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2010.549098
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0740817X.2010.549098?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. Ang, Marcus & Lim, Yun Fong, 2019. "How to optimize storage classes in a unit-load warehouse," European Journal of Operational Research, Elsevier, vol. 278(1), pages 186-201.
    3. Öztürkoğlu, Ö. & Gue, K.R. & Meller, R.D., 2014. "A constructive aisle design model for unit-load warehouses with multiple pickup and deposit points," European Journal of Operational Research, Elsevier, vol. 236(1), pages 382-394.
    4. Diefenbach, Heiko & Grosse, Eric H. & Glock, Christoph H., 2024. "Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1049-1068.
    5. Öztürkoğlu, Ömer & Hoser, Deniz, 2019. "A discrete cross aisle design model for order-picking warehouses," European Journal of Operational Research, Elsevier, vol. 275(2), pages 411-430.
    6. Yeliz Kocaman & Ömer Öztürkoğlu & Şevkinaz Gümüşoğlu, 2021. "Aisle designs in unit-load warehouses with different flow policies of multiple pickup and deposit points," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 323-355, March.
    7. Subir S. Rao & Gajendra K. Adil, 2017. "Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 327-346, January.
    8. Rakesh Venkitasubramony & Gajendra K. Adil, 2016. "Analytical models for pick distances in fishbone warehouse based on exact distance contour," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4305-4326, July.
    9. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).
    10. Cardona, Luis F. & Soto, Diego F. & Rivera, Leonardo & Martínez, Hector J., 2015. "Detailed design of fishbone warehouse layouts with vertical travel," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 825-837.

    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:43:y:2011:i:10:p:703-720. 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.