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Optimizing case-pack sizes in the bricks-and-mortar retail trade

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Abstract

Before reaching the store, products generally flow through the retail distribution system as larger bundles, the so-called case packs (CP). In several studies these case packs have been identified as having a significant impact on distribution logistics efficiency. In this paper we develop a quantitative model and solution approach determining optimal case-pack sizes for non-perishable products in grocery retailing. The model captures the relevant operative cost drivers along the internal supply chain of a large bricks-and-mortar retailer. It explicitly represents each day of the retailer’s business week, where the replenishment doctrine considered generalizes the well-known periodic review reorder point (r, s, nq) policy as a stationary cyclic version. Exact and approximate methods are developed to evaluate the costs of a model instance. In addition, an optimization procedure is outlined that uses either exact or approximate methods to identify optimal and near-optimal CP sizes for a single store as well as for a network of multiple stores to be operated with one common CP. Applied to real-world examples of a large European retail chain, the methods reveal average cost improvement potential of more than 20% by adjusting the CP sizes that are currently in use. The approach presented is thus shown to be a valuable addition to any integrative retail supply chain planning system. Its results are directly applicable to retail practice.

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Authors and Affiliations

  1. Department of Operations, Catholic University of Eichstätt-Ingolstadt, Auf der Schanz 49, 85049, Ingolstadt, Germany

    Thomas Wensing, Michael G. Sternbeck & Heinrich Kuhn

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  1. Thomas Wensing
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  2. Michael G. Sternbeck
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  3. Heinrich Kuhn
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Correspondence to Heinrich Kuhn.

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Wensing, T., Sternbeck, M.G. & Kuhn, H. Optimizing case-pack sizes in the bricks-and-mortar retail trade. OR Spectrum 40, 913–944 (2018). https://doi.org/10.1007/s00291-018-0515-5

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  • DOI: https://doi.org/10.1007/s00291-018-0515-5

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