A new hybrid weighted optimization model for multi criteria ABC inventory classification

Abstract

ABC analysis is a commonly used inventory classification technique which consists in dividing a set of inventory items into three categories: category A contains the most important items, category B includes the moderately important items and category C contains the least important ones. The purpose of this classification is to manage inventory items in an efficient way by relaxing controls on low valued items and applying more meticulous controls on high valued items. In this paper, we propose a new hybrid weighted optimization model which combines the usefulness of two well-known inventory classification models (ZF-model [13] and H-model [10]). To measure the performance of the proposed model with respect to some existing classification models, a comparative study—based on a service-cost analysis—is conducted.