Development of knowledge-based heuristic model for workload balance

This paper involves a study of developing an input control model. The objective of input control is to minimize shop flow times while meeting customer due dates by attempting to maintain balanced workload at each work center. A Knowledge-Based Heuristic (KBH) model employing an AI-based rule induction approach, called Learning-From-Example (LFE) technique, is devised to release work to the shop based on the rules induced by the rule induction module. The Example Database (EXDB), as an input to the rule induction module, is established by analyzing the results of the simulation model. The KBH model is compared with other methodologies offered in the literatures under various levels of shop complexity. The results of computer simulation experimentation show that the relative performance of the KBH model is superior to the other models with respect to flow time and due date performance regardless of whether the shop is complex or simple. [In Korean.]