Inverse and direct airfoil design using a multiobjective genetic algorithm

Some of the advantages and drawbacks of genetic algorithms applications to aerodynamic design are demonstrated. A numerical procedure for the aerodynamic design of transonic airfoils by means of genetic algorithms, with single-point, multipoint, and multiobjective optimization capabilities, is presented. In the ® rst part, an investigation on the relative ef® ciency of different genetic operators combinations is carried out on an aerodynamic inverse design problem. It is shown how an appropriate tuning of the algorithm can provide improved performances, better adaption to design space size and topology, and variables cross correlation. In the second part, the multiobjective approach to design is introduced. The problem of the optimization of the drag rise characteristics of a transonic airfoil is addressed and dealt with using a single point, a multipoint, and a multiobjective approach. A comparison between the results obtained using the three different strategies is ® nally established, showing the advantages of multiobjective optimization.