Abstract: A new hybrid optimization algorithm HSADE (hybrid self-adaptive differential evolution) based on differential evolution and radial basis function response surface was proposed aiming at aerodynamic optimization problems. Through combing the merits of response surface method's fast local searching ability and differential evolution's powerful global searching ability, the overall local and global search efficiency of HSADE were simultaneously enhanced. Several improvements were made on certain logics and strategies embedded in the processes of each sub-algorithm by proposing and utilizing strategies such as selection strategy based on double elimination and self-adaptive parameters. Having applied HSADE and several other typical optimization algorithms-NSGA-Ⅱ, MOPSO and multi-objective differential evolution to several benchmark functions, the results indicated HSADE was superior to other algorithms in most of the cases regarding local search ability represented by generation distance and global search ability symbolled by hyper volume ratio, which validated the effectiveness of above improvements. Applying HSADE along with basic DE and NARSGA to an airfoil optimization problem and a hypersonic nozzle expansion surface optimization problem, the results showed HSADE was able to obtain airfoils with extra 0.5 count drag reduction and nozzles with better performance than other two algorithms under approximately 1000 function evaluations, which indicated high engineering application potential of HSADE.