Rough Sets Based Product Mix Analysis

In this paper, the TOC approach to the product mix optimization is modeled using rough set theory. Rough set theory is a new mathematical tool for imperfect data analysis and supports approximations in decision-making. The product mix adjustments reduce the volume of some products to maximize the revenue by producing the products with high profitability. TOC heuristics provides a solution that is, implicit, and rough sets provide an explicit solution by rule extraction from the information system. The exact concepts described by lower and upper approximations are determined by an indiscernibility relation (equivalence) on the domain, which in turn may be induced, by a given set of attributes ascribed to the objects of the domain. The extensional description and intentional description is studied here for feature and rule extraction.