In order to improve the dynamic performance of high-speed trains, improve the running stability and safety, the multi-objective optimization design of train suspension system parameters was carried out with the optimization objectives of rail coefficient, wheel weight reduction rate and running stability. Based on the Kriging surrogate model theory, a high-precision approximation model was constructed, and a dynamic performance optimization platform for high-speed trains was developed. By improving the MOMSA multi-objective optimization algorithm, the global optimization of suspension system parameters was realized. The optimization results show that the optimized suspension parameters significantly improve the dynamic performance of the train, and the vertical stationarity index is the most significant, with an optimization range of 14.6%. At the same time, the optimization rate of wheel weight reduction rate, lateral stability and derailment coefficient is 10.7%, 8.4% and 5.3% respectively, which effectively improves the running quality and safety performance of the train.