A prototype intelligent model management system for inventory decision support

Inventory control is of prime importance in the management of operations. Researchers and practitioners have developed inventory techniques and models for various types of operating conditions. Unfortunately, this knowledge is not readily available in a form useful to practitioners. In this paper, the inventory literature is first organized by using a taxonomy that relates inventory models to the conditions under which they are applicable. This knowledge then serves as the basis of the intelligent model management system, which recommends applicable model(s) given a set of operating conditions. The prototype system helps practitioners to readily find appropriate inventory models and to understand their requirements, and serves as an effective teaching tool for learning and integrating the inventory literature. The prototype also allows for comparison of inventory models in innovative ways revealing helpful insights and possibly leading to future research ideas. Unlike earlier expert systems, this prototype efficiently searches for models based on the value of the products and with the help of its comprehensive taxonomy locates and distinguishes among a much larger range of models.