In order to ensure the coincidence between heat flux on the surface of the specimen during the dual gas flow combined thermal test and hypersonic aerodynamic heat flow, the test parameters were optimized. Numerical model of the dual gas flow combined heating for typical tip wedge structure was built, 128 samples were selected via the Latin Hypercube sampling method and the adding-point strategy based on fuzzy clustering, and numerical simulation was carried out. Then, Kriging surrogate model and elitist non-dominated sorting generic algorithm were applied in multi-objective optimization, which aimed at minimizing the difference between gas flow heating and hypersonic aerodynamic heating. The results showed that the error of surrogate model was significantly reduced by increasing samples. The maximum of mean relative errors of surface heat flux of 8 test samples was about 7%, and less than 5% in most areas, while the mean value of root mean square errors and the peak value of maximum errors were 1.72% and 13.6%, respectively, indicating that the Kriging surrogate model had high prediction accuracy. What’s more, through optimization, the distribution of surface heat flux by gas flow heating was in good agreement with that of hypersonic aerodynamic heat flow. The relative error of heat flux at stagnation was less than 1%, and no more than 10% at the flat plate area, which showed the effectiveness of parameters optimization of dual gas flow combined thermal test based on Kriging surrogate model.