KBLS: A prototype knowledge-based system for the selection of lot-sizing models

Abstract

Research in experimental simulation of multi-stage inventory systems shows that a poor choice of lot-sizing heuristics has a significant degree of cost penalty and schedule instability. A realistic approach to a multi-stage system is to choose a suitable technique for a certain special circumstance rather than trying for a single best heuristic covering all cases. To avoid serious cost penalties and high schedule instability caused by inferior techniques, knowledge-based system technology could help practitioners to make a sensible choice of heuristics. In this paper, we develop a prototype knowledge-based system whose aim is to provide an acceptable lot-size schedule in a limited time which would hopefully lead to a good master production schedule.