Adaptive genetic fuzzy, predictive and multiobjective approach for AGVs dispatching

Excellence in manufacturing systems has been recognized as one of the main factors behind the success of industrial companies. New technologies for manufacturing processes play a significant role in this process. Achieving the potential of technological innovations in production, however, requires a wide range of management, as well as engineering issues related to the system. Material handling is a key component in reaching flexibility, manufacturing, dynamism and agility goals. The handling capacity of advanced materials is essential because without this ability of providing the material needed for the proper workstation at the right time and in the right amount, the whole plant will become “bogged down”. This makes it less efficient and thus produces less profit and / or it operates at higher costs. This paper proposes a heuristic dispatching Automation Guided Vehicle (AGV) based on fuzzy logic and genetic algorithms. The proposal also includes prediction task, multi-objective and modeling Petri nets causing the closest simulation of real environment.