Efficient Global Optimization Method for Multipoint Airfoil Design

In the frame of an investigation about surrogate models employed in aerodynamic optimization problems, this work aims at illustrating the suitability of adapted design space sampling to evolutionary optimization. The adaptive sampling algorithm is based on the Weighted Expected Improvement idea applied to a Kriging-based meta-model. A multipoint airfoil optimization is set as test case. A deep investigation is devoted to the tuning of the weights of Expected Improvement function to enhance the performance of the optimization process. A comparison between a pure genetic optimization and a Weighted Expected Improvement approach is proposed. Efficiency and quality of the obtained results are discussed.