The work aims to study the effect law and interaction of high-speed milling parameters on the surface quality of aviation casting titanium alloy Ti-6Al-4V, and optimize the surface quality and material removal rate based on high-speed milling parameters. Box-Behnken design and quadratic regression orthogonal test were adopted to establish a significant no-fail regression model of surface roughness and high-speed milling parameters, and then obtain significant differences in the effects of milling parameters on surface roughness. On this basis, the relationship between interaction of high-speed milling parameters and surface roughness was explored. Based on surface roughness regression model and material removal rate, Genetic Algorithm (GA) was used for multi-objective optimization of high-speed milling parameters. The order of significance of the milling parameters affecting the surface roughness of the aviation casting titanium alloy Ti-6Al-4V specimen was:cutting depth > feed per tooth > cutting width > spindle speed, in which the interaction of cutting width and spindle speed, feed per tooth and spindle speed was more obvious in interaction. The values of surface roughness and material removal rate were improved by 44% and 70%, respectively after the optimization of milling parameters by GA. Therefore, the surface roughness of the specimen optimized by GA was significantly reduced, the surface toolpath row spacing was narrowed, and the average height of the texture was lowered. The experimental results indicate that the significant no-fail regression model of surface roughness established by response surface has high prediction accuracy, and the milling parameters optimized by GA can effectively improve the surface quality and cutting efficiency, which is a good guideline for ensuring the surface quality of aviation casting titanium alloy Ti-6Al-4V.