Clustering And Optimization Models for Commercial Decisions

Data mining as a technique is used to find interesting and valuable knowledge from huge amount of stored data within databases or data warehouses. It encompasses classification, clustering, association rule learning, etc., whose goal is to improve commercial decisions and behaviors in organizations. In this project, we built clustering and optimization models as a two-step sequential method. In the first step, the clustering model was used to segment customers into different clusters. While in the second step, our optimization model was utilized to produce different types of membership cards. Conclusively, this research provides a basis for customer segmentation and membership card generation in a hypermarket by way of data mining and optimization techniques. Through our research, fuzzy clustering method can be suitably used for customer segmentation in a real world application and optimization model can be appropriately used for membership card generation.