Dynamic selection of dispatching rules by fuzzy inference

Proposes a fuzzy inference-based selection of dispatching rules, adapting the scheduling decision to the dynamic changes in the manufacturing environment. In the proposed method, the performance of different dispatching rules is studied while varying production conditions. Environmental variables are then used to detect those changes, as input to the fuzzy inference system. The fuzzy inference will thereupon attribute preference levels to the dispatching rules, according to their adequacy to the current environment. The scheduling is made using partitioned combination of dispatching rules. In order to verify the validity of the proposed method, an application to FMS scheduling is presented.