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Hierarchical reasoning and knapsack problem modelling to design the ideal assortment in retail

Jocelyn Poncelet 1 Pierre-Antoine Jean 1 Michel Vasquez 1 Jacky Montmain 1
1 I3A - Informatique, Image, Intelligence Artificielle
LGI2P - Laboratoire de Génie Informatique et d'Ingénierie de Production
Abstract : The survival of a supermarket chain is heavily dependent on its capacity to maintain the loyalty of its customers. Proposing adequate products to customers is the issue of the store’s assortment. With tens thousands of products on shelves, designing the ideal assortment is theoretically a thorny combinatorial optimization problem. The approach we propose includes prior knowledge on the hierarchical organization of products by family to formalize the ideal assortment problem into a knapsack problem. The main difficulty of the optimization problem remains the estimation of the expected benefits associated to changes in the product range of products’ families. This estimate is based on the accounting results of similar stores. The definition of the similarity between two stores is then crucial. It is based on the prior knowledge on the hierarchical organization of products that allows approximate reasoning to compare any two stores and constitutes the major contribution of this paper.
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https://hal.mines-ales.fr/hal-02518764
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Submitted on : Wednesday, March 25, 2020 - 2:41:09 PM
Last modification on : Monday, August 10, 2020 - 1:51:29 PM

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Jocelyn Poncelet, Pierre-Antoine Jean, Michel Vasquez, Jacky Montmain. Hierarchical reasoning and knapsack problem modelling to design the ideal assortment in retail. IPMU 2020 - 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2020, Lisbonne, Portugal. pp.201-214, ⟨10.1007/978-3-030-50146-4_16⟩. ⟨hal-02518764⟩

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