In sheet metal forming process, the input process parameters scatter and considerably result in unreliablity in practical production. Optimization for sheet metal forming process is often considered as a multi-objective problem. An optimizition strategy for high strength steel (HSS) sheet metal forming process was suggested based on response surface methodology (RSM). Latin Hypercube Sampling (LHS) method was introduced to design the rational experimental samples; the objective function was defined based on cracking factor wrinkle factor and severe thinning factor; the accurate response surface for sheet metal forming problem was built by Least Square Method; Multi-objective Genetic Algorithm(MOGA) was adoped in optimization and Pareto solution was selected. The strategy was applied to analyze a HSS auto-part, the result has proved this method suitable for optimization design of HSS sheet metal forming process.