To improve Vehicle ride and handling characteristics. comfort of mining dump trucks under adverse road conditions, this paper conducts parameter optimization research on its key component—the hydro-pneumatic suspension system. Firstly, the suspension parameters are sampled using the Latin Hypercube method, and a vehicle dynamics model is constructed using MATLAB/Simulink to obtain the vehicle body vertical acceleration response under different working conditions. On this basis, a high-precision surrogate model between the suspension design parameters and the vehicle body vertical acceleration RMS, a key ride comfort metric is established based on the Kriging model. Furthermore, with the objective function of minimizing the RMS value of the vehicle body vertical acceleration, and considering the constraints of tire dynamic load and suspension dynamic deflection, a parameter optimization model for the hydro-pneumatic suspension system is established. The genetic algorithm is employed to solve this model, achieving the global optimization of the initial gas pressure and initial gas volume in the front accumulator and rear suspensions, and the damping orifice diameter. The research results show that after optimization by the genetic algorithm, the RMS value of vertical dynamics of the vehicle body acceleration is significantly reduced under both no-load and full-load states, when driving on Grade D and Grade E roads at different speeds. The maximum optimization improvement rate reaches 67.3%, effectively proving the effectiveness and practicality of the proposed optimization method in enhancing vehicle ride performance. This provides multiple sets of optimal passive parameters forming a lookup table for the subsequent design of active control strategies.