IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v41y2009i3p194-208.html
   My bibliography  Save this article

Optimal zone boundaries for two-class-based compact three-dimensional automated storage and retrieval systems

Author

Listed:
  • Yugang Yu
  • René de Koster

Abstract

Compact, multi-deep three-dimensional (3D), Automated Storage and Retrieval Systems (AS/RS) are becoming more common, due to new technologies, lower investment costs, time efficiency and compact size. Decision-making research on these systems is still in its infancy. This paper studies a particular compact system with rotating conveyors for the depth movement and a Storage/Retrieval (S/R) machine for the horizontal and vertical movement of unit loads. The optimal storage zone boundaries are determined for this system with two product classes: high- and low-turnover, by minimizing the expected S/R machine travel time. We formulate a mixed-integer non-linear programming model to determine the zone boundaries. A decomposition algorithm and a one-dimensional search scheme are developed to solve the model. The algorithm is complex, but the results are appealing since most of them are in closed-form and easy to apply to optimally layout the 3D AS/RS rack. The results show that the S/R machine travel time is significantly influenced by the zone dimensions, zone sizes and ABC curve skewness (presenting turnover patterns of different products). The presented results are compared with those under random storage and it is shown that significant reductions of the machine travel time are obtainable by using class-based storage.[Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix]

Suggested Citation

  • Yugang Yu & René de Koster, 2009. "Optimal zone boundaries for two-class-based compact three-dimensional automated storage and retrieval systems," IISE Transactions, Taylor & Francis Journals, vol. 41(3), pages 194-208.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:3:p:194-208
    DOI: 10.1080/07408170802375778
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07408170802375778
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07408170802375778?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. Qu, T. & Huang, George Q. & Zhang, Yingfeng & Dai, Q.Y., 2010. "A generic analytical target cascading optimization system for decentralized supply chain configuration over supply chain grid," International Journal of Production Economics, Elsevier, vol. 127(2), pages 262-277, October.
    2. Xianhao Xu & Bipan Zou & Guwen Shen & Yeming (Yale) Gong, 2016. "Travel-time models and fill-grade factor analysis for double-deep multi-aisle AS/RSs," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4126-4144, July.
    3. Dong, Wenquan & Jin, Mingzhou, 2024. "Automated storage and retrieval system design with variant lane depths," European Journal of Operational Research, Elsevier, vol. 314(2), pages 630-646.
    4. Yang, Jingjing & de Koster, René B.M. & Guo, Xiaolong & Yu, Yugang, 2023. "Scheduling shuttles in deep-lane shuttle-based storage systems," European Journal of Operational Research, Elsevier, vol. 308(2), pages 696-708.
    5. Gharehgozli, Amir & Xu, Chao & Zhang, Wenda, 2021. "High multiplicity asymmetric traveling salesman problem with feedback vertex set and its application to storage/retrieval system," European Journal of Operational Research, Elsevier, vol. 289(2), pages 495-507.
    6. Nima Zaerpour & Yugang Yu & René B.M. de Koster, 2017. "Optimal two-class-based storage in a live-cube compact storage system," IISE Transactions, Taylor & Francis Journals, vol. 49(7), pages 653-668, July.
    7. Mirzaei, Masoud & Zaerpour, Nima & de Koster, René, 2021. "The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    8. Boysen, Nils & Briskorn, Dirk & Emde, Simon, 2017. "Sequencing of picking orders in mobile rack warehouses," European Journal of Operational Research, Elsevier, vol. 259(1), pages 293-307.
    9. Nima Zaerpour & Yugang Yu & René de Koster, 2017. "Small is Beautiful: A Framework for Evaluating and Optimizing Live-Cube Compact Storage Systems," Transportation Science, INFORMS, vol. 51(1), pages 34-51, February.
    10. Silva, Allyson & Roodbergen, Kees Jan & Coelho, Leandro C. & Darvish, Maryam, 2022. "Estimating optimal ABC zone sizes in manual warehouses," International Journal of Production Economics, Elsevier, vol. 252(C).
    11. Nima Zaerpour & Yugang Yu & René B. M. de Koster, 2017. "Response time analysis of a live-cube compact storage system with two storage classes," IISE Transactions, Taylor & Francis Journals, vol. 49(5), pages 461-480, May.
    12. Jianglong Yang & Li Zhou & Huwei Liu, 2021. "Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-25, April.
    13. Yang, Peng & Yang, Kaidong & Qi, Mingyao & Miao, Lixin & Ye, Bin, 2017. "Designing the optimal multi-deep AS/RS storage rack under full turnover-based storage policy based on non-approximate speed model of S/R machine," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 113-130.
    14. Wenquan Dong & Mingzhou Jin & Yanyan Wang & Peter Kelle, 2021. "Retrieval scheduling in crane-based 3D automated retrieval and storage systems with shuttles," Annals of Operations Research, Springer, vol. 302(1), pages 111-135, July.

    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:41:y:2009:i:3:p:194-208. 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.