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

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  • 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
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    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. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. 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.

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