A strategy of production scheduling with the fitness function of genetic algorithm using Timed Petri net and considering AGV and the input buffer

Scheduling of machines and AGVs in Flexible Manufacturing Systems involves modeling and searching methodology in a wide solution space. In this work the search for scheduling occurs by genetic algorithm and simple AGV dispatching rules. Modeling occurs in Timed Petri nets in time of fitness evaluation, considering the input buffers of machines, AGVs, and flags also control the use of these buffers, which avoids deadlock. We consider the input buffer of the machines as being of size 1 and allowed to advance transport using them, seeking to optimize the minimum makespan. The proposal was tested in two scenarios of FMS and validated by comparing its results with two others obtained by techniques based on genetic algorithm and adaptive genetic algorithm.