Route Planning for Multiple AGV System Using Genetic Algorithm in Manufacturing Warehouse

Many scholars have proved that path planning in a multiple automated guided vehicle (AGV) system is an NP-Hard issue. Traditionally, numerous mathematical strategies have been used to complete this difficult task. Based on a genetic algorithm, this research provides an efficient path planning solution for many AGV systems. The constraint in the optimization task is that, each AGV starts and returns to his starting place, minimizing single path distance of each Agv.Travelling to a unique set of pick-up stations, each pick-up station is visited by exactly one AGV for goods picking up. The Cost Function is to search for the shortest path the least distance needed for each AGV to travel from the start location to individual points and back to the original starting place. The experimental results show that the total path distance of all AGVs and longest Single AGV path distance are shortened by using the modified genetic algorithm.