Article ID: | iaor19992857 |
Country: | United Kingdom |
Volume: | 36 |
Issue: | 9 |
Start Page Number: | 2497 |
End Page Number: | 2509 |
Publication Date: | Sep 1998 |
Journal: | International Journal of Production Research |
Authors: | Yih Y., Min H.-S., Kim C.-O. |
Keywords: | scheduling, neural networks |
In this paper, we propose an integrated approach of inductive learning and competitive neural networks for developing multi-objective flexible manufacturing systems (FMS) schedulers. Simulation and competitive neural networks are applied sequentially to extract a set of classified training data which is used to create a compact set of scheduling rules through inductive learning. The FMS scheduler can assist the operator to make decisions in real time, while satisfying multiple objectives desired by the operator. A simulation-based experiment is performed to evaluate the performance of the resulting scheduler.