This paper presents a new intelligent path planning and scheduling method for automated guided vehicles in a flexible manufacturing system. The main objective is to minimize the total distance traveled by a loaded vehicle. The path planning and scheduling algorithm is coded in MATLAB~® using evolutionary algorithm. The proposed algorithm has considerable advantages over a number of previous efforts and produces reasonably good results very quickly and hence can be used for real time planning and scheduling of automated guided vehicles. The evolutionary algorithm presented is also flexible, in the sense that it can be used for any number of vehicles and any number of machines in the shop floor with slight modifications.
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