Abstract
With few historical data and quick response of the market, fast fashion apparel retailers should make decisions about replenishment policies and assortment strategies. Deciding the quantity to deliver for each point of sales, in term of quantity and assortment mixture, is one of the big retailers challenges, and keys of success. In this paper, our proposal is about a mathematical model, for fast fashion retail planning chain. Our model is a dynamic tool to make the loop on the assortment, replenishment and inventory quantities, to help decision makers delivering the right product in the right point of sales with the right quantity, by maximizing the profit. It constitutes a flexible tool, allowing retailer to add new items in the optimization process, or even to renew the product range regularly, for fast fashion retailers, who aim for just in time production models. The replenishment supply chain is fragmented into strategic, tactic and operational levels. Each level is modeled as an integer linear program. Looping is made from Head Quarters, through countries until stores. Chorological horizon is sub divided according to season collections, monthly and weekly basis. Our integer linear programs are developed and solved with IBM Cplex Optimizer. Model validation is established with random data instances, inspired from real case studies.
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Fares, N., Lebbar, M., Sbihi, N. (2019). Fast Fashion Retail: Dynamic Sub-models for Replenishment and Assortment Problem. In: Rinaldi, R., Bandinelli, R. (eds) Business Models and ICT Technologies for the Fashion Supply Chain. IT4Fashion 2017. Lecture Notes in Electrical Engineering, vol 525. Springer, Cham. https://doi.org/10.1007/978-3-319-98038-6_9
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DOI: https://doi.org/10.1007/978-3-319-98038-6_9
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