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The discrete forward–reserve problem – Allocating space, selecting products, and area sizing in forward order picking

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  • Walter, Rico
  • Boysen, Nils
  • Scholl, Armin

Abstract

To reduce labor-intensive and costly order picking activities, many distribution centers are subdivided into a forward area and a reserve (or bulk) area. The former is a small area where most popular stock keeping units (SKUs) can conveniently be picked, and the latter is applied for replenishing the forward area and storing SKUs that are not assigned to the forward area at all. Clearly, reducing SKUs stored in forward area enables a more compact forward area (with reduced picking effort) but requires a more frequent replenishment. To tackle this basic trade-off, different versions of forward–reserve problems determine the SKUs to be stored in forward area, the space allocated to each SKU, and the overall size of the forward area. As previous research mainly focuses on simplified problem versions (denoted as fluid models), where the forward area can continuously be subdivided, we investigate discrete forward–reserve problems. Important subproblems are defined and computation complexity is investigated. Furthermore, we experimentally analyze the model gaps between the different fluid models and their discrete counterparts.

Suggested Citation

  • Walter, Rico & Boysen, Nils & Scholl, Armin, 2013. "The discrete forward–reserve problem – Allocating space, selecting products, and area sizing in forward order picking," European Journal of Operational Research, Elsevier, vol. 229(3), pages 585-594.
    • Handle: RePEc:eee:ejores:v:229:y:2013:i:3:p:585-594
    DOI: 10.1016/j.ejor.2013.02.047
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    Cited by:

    1. Leung, Eric K.H. & Lee, Carmen Kar Hang & Ouyang, Zhiyuan, 2022. "From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management," International Journal of Production Economics, Elsevier, vol. 244(C).
    2. Jiang, Min & Huang, George Q., 2022. "Intralogistics synchronization in robotic forward-reserve warehouses for e-commerce last-mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    3. Lam, H.Y. & Ho, G.T.S. & Mo, Daniel Y. & Tang, Valerie, 2023. "Responsive pick face replenishment strategy for stock allocation to fulfil e-commerce order," International Journal of Production Economics, Elsevier, vol. 264(C).
    4. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    5. Guo, Xiaolong & Chen, Ran & Du, Shaofu & Yu, Yugang, 2021. "Storage assignment for newly arrived items in forward picking areas with limited open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    6. Dragan Djurdjević & Nenad Bjelić & Dražen Popović & Milan Andrejić, 2022. "A Combined Dynamic Programming and Simulation Approach to the Sizing of the Low-Level Order-Picking Area," Mathematics, MDPI, vol. 10(20), pages 1-23, October.
    7. Jiang, Min & Leung, K.H. & Lyu, Zhongyuan & Huang, George Q., 2020. "Picking-replenishment synchronization for robotic forward-reserve warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    8. David Winkelmann & Frederik Tolkmitt & Matthias Ulrich & Michael Romer, 2022. "Integrated storage assignment for an e-grocery fulfilment centre: Accounting for day-of-week demand patterns," Papers 2209.03998, arXiv.org, revised May 2023.

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