Airfoil and wing design through hybrid optimization strategies

Real-world design problems need robust and effective system level optimization tools inasmuch as they are ruled by several criteria, most often in multidisciplinary environments. In this work a hybrid optimization algorithm has been obtained by adding a gradient-based technique to the set of operators of a multiobjective genetic algorithm. This makes it possible to increase the computational efficiency of the genetic algorithm while preserving its favorable features of robustness, problem independence, and multiobjective optimization capabilities. Aerodynamic shape design problems, including both airfoil and wing designs, are considered.