Abstract: Objective: In order to improve the load balance of the MVB (multi\|functional vehicle bus) periodic scheduling table for rail vehicles, increase the utilization of MVB bandwidth, and achieve the real\|time performance of the vehicle's communication system, it is necessary to optimize the MVB periodic scheduling table. Method: The principle of MVB periodic information communication is briefly introduced, the two constraints of MVB scheduling table are clarified, a theoretical method for applying MCTS (Monte Carlo Tree Search) algorithm to MVB scheduling table optimization is established, and the algorithm through Python software programming is implemented. The optimization objectives of the MCTS algorithm are clarified, and a pruning strategy for optimizing the MCTS algorithm is designed based on the constraints of the MVB scheduling table. Three algorithms, RMS (Monotonic Rate Scheduling) algorithm, MCTS algorithm, and GA (Genetic Algorithm), are selected for simulation experiments, and the results of each algorithm are compared and analyzed. Result &Conclusion: The optimized MCTS algorithm effectively avoids a large number of invalid searches with a very high search efficiency. Compared with RMS algorithm and GA, the optimized MCTS algorithm can obtain more balanced solutions within the same search time. If the number of vehicle communication devices increases and a scheduling table containing more variables needs to be generated, the advantages of the MCTS algorithm in searching can be further highlighted.