Integration of inductive learning and neural networks for multi-objective FMS scheduling

Integration of inductive learning and neural networks for multi-objective FMS scheduling

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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: , ,
Keywords: scheduling, neural networks
Abstract:

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.

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