A structured expert system for model management in inventory control

The focus of this paper is on the expert system design for inventory control model management. The model selection procedure uses the knowledge of inventory theory as well as user-specific heuristics and approximation rules. The models available in the model base are represented in a model selection tree using information currently present in the inventory control literature. We explore the use of a structured design methodology through incorporating knowledge modules (i.e. sub-expert system) at the nodes of the model selection tree. The knowledge base is also modularized into selection, application, and solution knowledge bases in addition to a database, each with its unique and independent set of rules and/or storage requirements. This structured design reduces the knowledge representation complexity, facilitates the search process and allows for the use of backtracking procedures to select approximate models for the problem. Implementation of the system using the expert system shell GURU is discussed and sample consultation is provided in the appendix.