Genetic Algorithms and Game Theory for High Lift Multi-Airfoil Design Problems in Aerodynamics

This paper presents a multi-objective evolutionary optimization method combining Genetic Algorithms (GAs) and Game Theory (GT) for high lift multi-airfoil systems in Aerospace Engineering. GAs are IT based evolutionary methods introduced by J.H. Holland for mimicking natural adaptation systems in the computer. Due to large dimension global optimization problems and the increasing importance of low cost distributed parallel environments it is a natural idea to replace a global optimization by decentralized local sub-optimizations using GT which introduces the notion of games associated to an optimization problem. This GT/GAs combined optimization method is developed in this paper and used for reconstruction and optimization problems applied to high lift multi-airfoil design. Numerical results obtained with this new approach are compared favorably with single global GAs’ ones and illustrate the promising robustness and efficient parallel properties of coupled GAs with different game scenarios for future advanced multidisciplinary aerospace technologies.