Catalog segmentation with double constraints in business

Catalog segmentation is an important issue in data mining in business from the microeconomic point of view. In catalog segmentation, an enterprise tries to develop k catalogs with r products that are sent to corresponding customers in order to maximize the overall number of catalog products purchased. In this paper, a novel model called catalog segmentation problem with double constraints (DCCSP) is presented. In this model, the interest constraint is minimized and the profit constraint is maximized so that the profit of products purchased by customers who have at least t interesting products in receiving catalogs is maximized. The complexity of the DCCSP is analyzed, and a DCCS algorithm to solve the optimization is proposed. The experimental results show that the proposed algorithm is efficient and can be used to solve the DCCSP effectively.