Intelligent mining is the mainstream direction of the future development of open-pit mines.Eelectric shovel is the main production equipment of open-pit mines，so the study of electric shovel autonomous shoveling technology is one of the core steps to realize the intelligent mining of open-pit mines in the future.During the autonomous shoveling process，the electric shovel uses its excavation mechanism，shovels the ore out of the mine and dumps the ore into a transport truck that the ore has been parked at the dump position.When the shovel has finished loading the ore shovel in the corresponding mining area of the current working position，it will slowly move through its moving mechanism to the next position point and continue to shovel the ore pile in the target area.Because of the huge volume of the electric shovel itself，the continuous work of the excavation mechanism and the moving mechanism consume a lot of electric energy. In order to improve the efficiency of the electric shovel in the process of autonomous shoveling，reduce the energy consumption of the electric shovel work，this paper proposed a method of optimizing the moving route of the shovel，by planning the electric shovel moving route and digging area，shortening the length of the electric shovel moving route.A method for optimizing the mobile route of electric shoveling was proposed.On the basis of the known electric shovel working area，in order to excavate all the ore piles in the working area and the electric shovel moves the least number of times，greedy algorithm was used to plan the set of job locations where the shovel moves the least number of times.By increasing the transition point and other ways to further optimize the electric shovel movement path and adjust the corresponding mining area planning，to form the optimal trajectory of the final electric shovel operation.Selecting the ore pile after blasting in an area in a mine aerial map as an electric shovel to be shoveled，based on the above method， the mobile route of electric shovel loading was optimized.The results show that the total distance of the generated electric shovel moving path is short，and the planned excavation area meets the actual production requirements，which proves that the method can provide guidance for the movement trajectory planning of the autonomous shovel.