Recently several authors have concentrated their efforts in developing models to determine the economic lot size for multi‐stage systems. This is due to the fact that an increasing number of organisations are implementing material requirements planning systems. Numerous models have been developed and tested on problems with finite and rolling horizons and with deterministic time varying demand patterns.

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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.