Ramnath Vaidyanathan

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We consider the problem of choosing, from a set of N potential SKUs in a retail category, K SKUs to be carried at each store so as to maximize sales or a defined profit function. Assortments can vary by store, subject to a maximum number of different assortments. We describe an approach in which we view a SKU as a set of attribute values, use sales history(More)
R E TA I L D E M A N D M A N A G E M E N T : F O R E C A S T I N G , A S S O R T M E N T P L A N N I N G A N D P R I C I N G Ramnath Vaidyanathan Marshall Fisher In the first part of the dissertation, we focus on the retailer’s problem of forecasting demand for products in a category (including those that they have never carried before), optimizing the(More)
In the first part of the dissertation, we focus on the retailer's problem of forecasting demand for products in a category (including those that they have never carried before), optimizing the selected assortment, and customizing the assortment by store to maximize chain-wide revenues or profits. We develop algorithms for demand forecasting and assortment(More)
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