IEEE International Conference on Knowledge Engineering and Applications (ICKEA), Singapore, Singapore, 28 - 30 September 2016, pp.245-250
Based on empirical insights, quantitative decision support systems and the need for more advanced models reflecting category managers' actual decision problems is inevitable. The objective of this paper is to develop retail shelf space management using simulation based optimization. The focus of this research is therefore to examine retail shelf space problems and develop an optimization model to maximize the profitability of a retail haircare products category. The numerical optimization is performed on the category profitability. Exogenous Substitution Model which is one of the assortment models to calculate category profitability is used. The focus point of the model is to decide which product should be listed on the products substitutability. Besides stock levels of products should be calculated. Also, in this model for shelf allocating, an extra decision variable is calculating positions of products. The case study is covering the application of the proposed model in a supermarket.