Application of the genetic algorithm to design path direction for automated guided vehicle’s movement network

Automated guided vehicle (AGV) systems influence the efficiency and cost of flexible manufacturing systems. Design of the AGV’s guide path is a feature that affects the efficiency of the system, and a good design can reduce material handling cost in manufacturing. The path design problem for AGV’s movement network has been solved using several approaches. In this research a new technique, the genetic algorithm, is applied to the path design problem in which the appropriate travel direction for the AGV is determined. The objective of the research is to minimize the total distance traveled by loaded and unloaded vehicles. To calculate the total distance, a branch-and-bound technique with breadth first search is applied in the research. The effects of loaded and unloaded movements are considered simultaneously. The genetic algorithm approach achieved good results, when applied to the total loaded and unloaded vehicle distance. In conclusion, the genetic algorithm can be applied to design path direction for AGV’s movement network.