Missile aerodynamic shape optimization using genetic algorithms

The use of pareto genetic algorithms (GAs) to determine high-efficiency mis sile geometries is examined, and the capability of these algorithms to dete rmine highly efficient and robust missile aerodynamic designs is demonstrat ed, given a variety of design goals and constraints. The design study prese nted documents both the learning capability of GAs and the power of such al gorithms for multiobjective optimization. Results indicate that the GA is c learly capable of designing aerodynamic shapes that perform well in either single or multiple goal applications.