In today's retail environment, there are many consumer packaged goods (CPG) in the same category with various brands and differential products under the same brand. These differential products appear in different dimension sizes, display facing areas, purchasing costs and selling prices which are competing for a limited space in retail store shelves. Product assortment and space allocation of the chosen products to a limited shelf space is becoming more and more important for retailers. In this thesis we critically review the existing literature of shelf space allocation optimization models and solution techniques. We then propose a comprehensive model for shelf space allocation for a product category. Products are allocated to a two-dimensional area of a shelf section where a shelf section consists of multilevel vertical shelves. We account for adjustable shelf heights and product and brand integrity in a shelf section. Unlike the existing optimization models in the literature, we model our demand not only as a function of the space allocated to a product, in terms of the number of display facings, but also as a function of vertical product location in a shelf section and price sensitivity. Stackability of the products is also considered and products can be stacked depending on their package. Our objective is to maximize the retailer's daily gross profit. We numerically show that incorporating price changes and adjustable shelf spaces can have major impacts on the retailers' profit. Finally, we provide directions and suggestions for future research in this growing area of research.

Master of Applied Science (MASc)