A Multiobjective Approach to Transonic Wing Design by Means of Genetic Algorithms

In this work a transonic wing design problem is faced by means of a multiobjective genetic algorithm, and using a full potential flow model. The applications here presented regard both planform and wing section optimization. It is shown how both geometric and aerodynamic constraints can be taken into account, and how the multiobjective approach to optimization can be an effective way to handle conflicting design criteria. An interpolation technique allowing a better approximation of Pareto fronts is described. Two possible ways of improving the computational efficiency of the genetic algorithm, namely a parallel implementation of the code and a hybrid optimization approach, are presented.
Presented at Symposium of RTO Applied Vehicle Technology Panel (AVT) Canada, 18-21 Oct 1999, p22-1/22-12. This article is from ADA388284 Aerodynamic Design and Optimisation of Flight Vehicles in a Concurrent Multi-Disciplinary Environment (la Conception et l'optimisation aerodynamiques des vehicules aeriens dans un environnement pluridisciplinaire et simultane)