A method has been developed to efficiently implement supersonic aerodynamic predictions from Euler solutions into a highly constrained, multidisciplinary design optimization of a High-Speed Civil Transport. The method alleviates the large computational burden associated with performing computational fluid dynamics analyses through the use of variable-complexity modeling techniques, response surface methodologies, and coarse grained parallel computing. Using information gained from lower fidelity aerodynamic models, reduced term response surface models representing a correction to the linear theory response surface model predictions are constructed using Euler solutions. Studies into five, ten, fifteen, and twenty variable design problems show that accurate results can be obtained with the reduced term models at a fraction of the cost of creating the full term quadratic response surface models. Specifically, a savings of 255 CPU hours out of 392 CPU hours required to create the full term response surface model is obtained for the twenty variable problem on a single 75 MHz IP21 processor of a SGI Power Challenge.