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Modelling and performance evaluation of explosive storage policies in internet fulfilment warehouses

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  • Sevilay Onal
  • Jingran Zhang
  • Sanchoy Das

Abstract

Internet Fulfilment Warehouses (IFWs) are designed to exclusively process online retail orders. An observational study reveals that IFW operating and design attributes are significantly different from traditional warehouses in their storage and fulfilment policies. Specifically, we identify six IFW differentiators: explosive storage, very large number of beehive storage locations, bins with commingled SKUs, immediate fulfilment, short picking routes with single unit picks and high transactions with total digital control. Explosive storage of incoming bulk allows for faster fulfilment of customer orders often within a few hours. A new IFW control model is developed. This describes the associated receiving and fulfilment flows. Two decision algorithms for generating (i) a stocking list and (ii) an order picking list are presented. A simulation model was built to evaluate the fulfilment performance of the explosive policy. Experimental runs on a problem with 400 SKUs, 3240 bins and 22,000 customer orders over nine days are reported. Results show that increasing levels of explosion reduce the linear fulfilment time by as much as 16%, confirming the IFW storage policy is advantageous. The results also show that fulfilment time behaviour is convex as a function of the maximum number of stops allowed by the picking algorithm parameter.

Suggested Citation

  • Sevilay Onal & Jingran Zhang & Sanchoy Das, 2017. "Modelling and performance evaluation of explosive storage policies in internet fulfilment warehouses," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 5902-5915, October.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:20:p:5902-5915
    DOI: 10.1080/00207543.2017.1304663
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    Cited by:

    1. Onal, Sevilay & Zhu, Wen & Das, Sanchoy, 2023. "Order picking heuristics for online order fulfillment warehouses with explosive storage," International Journal of Production Economics, Elsevier, vol. 256(C).
    2. Zhong, Shuya & Giannikas, Vaggelis & Merino, Jorge & McFarlane, Duncan & Cheng, Jun & Shao, Wei, 2022. "Evaluating the benefits of picking and packing planning integration in e-commerce warehouses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 67-81.
    3. Nilendra Singh Pawar & Subir S. Rao & Gajendra K. Adil, 2024. "Improving Order-Picking Performance in E-Commerce Warehouses through Entropy-Based Hierarchical Scattering," Sustainability, MDPI, vol. 16(14), pages 1-27, July.
    4. Zhang, Jingran & Onal, Sevilay & Das, Sanchoy, 2020. "The dynamic stocking location problem – Dispersing inventory in fulfillment warehouses with explosive storage," International Journal of Production Economics, Elsevier, vol. 224(C).
    5. Xie, Lin & Thieme, Nils & Krenzler, Ruslan & Li, Hanyi, 2021. "Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 288(1), pages 80-97.
    6. Jin, Ming & Li, Gang & Cheng, T.C.E., 2018. "Buy online and pick up in-store: Design of the service area," European Journal of Operational Research, Elsevier, vol. 268(2), pages 613-623.
    7. Jianming Cai & Xiaokang Li & Yue Liang & Shan Ouyang, 2021. "Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 13(10), pages 1-26, May.

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