To analyse and improve the disturbance behaviour of the track chassis to the sand-gravel pavement during the steering process of the electric shovel, the steering process of the electric shovel is taken as the specific analysis object, and the steering radius, the steering velocity, the grouser width, and the grouser height are regarded as influence factors. The disturbance prediction model of the electric shovel is established through the coupling method of discrete element method (DEM) and multi-body dynamics (MBD) and the Kriging model. On this basis, the steering disturbance behaviours of the track chassis to the sand-gravel pavement under different working conditions are obtained. Finally, taking variation coefficient ratio of ground pressure, power, and disturbance potential energy as the optimization goal, the multi-objective optimization based on genetic algorithm (GA) and the disturbance prediction model is implemented, and the corresponding optimization results are 6.02 m, 0.14 m/s, 19.61 mm, and 12.68 mm. The feasibility of the optimization results is then confirmed via comparison with ones of DEM-MBD coupling simulation, the results show that the variation coefficient ratio of ground pressure, power, and disturbance kinetic energy are reduced to varying degrees, and the disturbance potential energy is greatly improved. This indicates that the disturbance of the track chassis to the sand-gravel pavement has been improved, which is conducive to better steering of the electric shovel.