Vehicle hood design is a typical multi-disciplinary task. The hood has to meet the demands of different attributes like safety, dynamics, statics, and NVH (Noise, Vibration, Harshness). Multi-disciplinary optimization (MDO) of vehicle hood at early design phase is an efficient way to support right design decision and avoid late-phase design changes. However, due to lacking in CAD models, it is difficult to realize MDO at early design phase. In this research, a new method of design and optimization is proposed to improve the design efficiency. Firstly, an implicit parametric hood model is built to flexibly change shape and size of hood structure, and generate FE models automatically. Secondly, four types of stiffness analysis, one type of modal analysis, together with pedestrian head impact analysis were established to describe multi-disciplinary concern of vehicle hood design. Finally, a platform is developed to integrate parametric modeling and CAE software to automatically conduct design of experiment (DOE) sampling, undertaking sensitivity analysis and find the optimal result. The results show that application of this method results in weight reduction from 16.8 kg to 14.83 kg and improves pedestrian protection performance score from 6.57 to 7.74 at the same time according to the China New Car Assessment Program (CNCAP).