Genetic learning of fuzzy rules applied to sequencing problem of FMS

Several techniques have been used for the determination of a good sequencing of parts that are stored in queues waiting for be processed. These techniques aim to improve the use of factory´s resources, to increase the productivity, to decrease the lead time, to maintain the delivery date, etc. In this context, this work presents an approach that use fuzzy system to set a more suitable parts sequencing to be processed at the machines. The fuzzy rule base of this system is generated from data using a genetic algorithm. In order to test and validate the proposed approach, a shop floor was tested using the fuzzy system obtained