Paper Title
A Cluster based Model for Assortment Optimization and Implementation in Home Improvement Retailer

Abstract
Abstract - This study deals with the clustering and mixed integer programming methods for the assortment optimization problem. The collaborative filtering method is used to estimate the parameters to be optimized. In addition, in the absence of a product, either substitute or complementary product effect is integrated into demand estimation. The basket analysis method is used to determine complementary products. The developed model is implemented in Turkey's leading home improvement retailer. Keywords - Assortment Optimization, Clustering, Collaborative Filtering, Demand Estimation, Retailing