基于混合遗传算法和复合形法的翼型优化设计

遗传算法的缺点在于计算过多的目标函数适应值而增加了优化设计的计算量。为了提高遗传算法的优化效率，将遗传算法和复合形法相结合，建立了基于混合遗传算法和复合形法的气动优化设计方法，对超临界翼型进行了单目标和多目标的优化设计，流场计算采用雷诺数平均N-S方程。算例表明，该设计优化方法稳定，设计质量高，效率比单纯遗传算法有很大提高，在工程中有较大的应用价值。

Optimization Design of Airfoil Based on Hybrid Genetic Algorithm and Compound Form Method

Genetic algorithm has a primary disadvantage that computational cost increases greatly for over much evaluation of objective functions and their fitness. To improve efficiency of optimization by means of genetic algorithm, a hybrid genetic algorithm and compound form method in aerodynamic optimization design is constructed by combining compound form method with genetic algorithm. The hybrid method is used to carry out single objective and multiple objectives aerodynamic optimization design of supercritical airfoil. The flow field is solved by Renolds -averaged N-S equations. The examples indicate that the hybrid method is stable and high efficient and the designed airfoil has a high quality. It is proved that the hybrid method is valuable on project application.