RGV optimal scheduling scheme selection in multi-process scenario

In this paper, the Rail Guide Vehicle (RGV) intelligent scheduling problem is solved by combining simulation and genetic algorithm. The optimal scheduling path under different machine assignment schemes is obtained. The simulation model is used to simulate the running process of RGV trolley, which can fully simulate various problems faced by RGV trolley in the actual operation process, which is of great practical significance. At the same time, using genetic algorithm to solve the simulation model, the optimal scheduling path can be approached step by step, and the optimization of scheduling scheme can be realized. In the solving process, we simulated the actual situation of 8 Computer Number Controller (CNC) and one RGV. 2^8-2 = 254 CNC scheme under the optimal path selection. In the simulated 254 allocation schemes, there were 16 cases with the highest efficiency, which was 23.13 units per hour. There are 2 cases with the lowest efficiency, and the efficiency is 7.10 units per hour.