Application of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft

The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution, stiffness distribution and design sensitivity. The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software. In the hybrid algorithm, the genetic algorithm is used to perform global search to avoid to fall into local optima, and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima. Moreover, the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed, which satisfy multiple constraints of strength, displacement, aileron efficiency, and flutter speed. The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase, and the optimization results are very consistent. Therefore, the design modifications can be decreased using the genetic/gradient-based hybrid algorithm.