Abstract

The scheduling of flexible manufacturing systems has received great importance as a key factor to improve competitiveness in industrial systems. In this paper it is presented an improvement of a two-phase optimization algorithm for Timed Coloured Petri Nets. The algorithm explores the compacted state space of manufacture models in order to find particular objective states giving the sequence of events that drives the model to the objective state with optimal times. The proposed approach is improved with the implementation of a time driven algorithm based on the shortest processing time which defines the successor states to be evaluated when time is used as a cost function. The developed algorithm is tested with benchmarks problems to demonstrate its efficiency to cope with models of combinatorial nature.

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