With the train speed becoming faster and faster, the aerodynamic drag turns to be one of the essential factor that restricts the train speed ascent. However, no public literature, abroad or abroad, has dealt with the flow field and aerodynamic performance of the train with the speed reaching 500km per hour. In this paper, an optimization study is carried out to reduce the aerodynamic drag of the high speed train (HST). First of all, a grid-based method is presented to parameterize the head shape of the HST, key variables are obtained by sensitivity analysis. Next, a response surface is constructed based on computational fluid dynamics (CFD) analysis to approximate the relationship of the drag and design variables at 500KPH. Finally, the genetic algorithm is used to optimize the head shape of the HST.