Learning based dynamic approach to job-shop scheduling

Dynamic selection of scheduling rules during real operations has been recognized as a promising approach to the scheduling of the production. This paper studies the dynamic job-shop scheduling and presents a fuzzy logic based learning approach. Experiment results show that the presented method outperforms the basic rules which are proved to perform well for such problem and that the proposed approach computes quickly enough to meet the requirements of dynamic scheduling.