多目标翼型优化设计基因算法研究

本文把基因算法用于多目标翼型优化设计，针对基因算法的搜索原理和气功外形特点，提出了与之相适应的Ｂｅｚｉｅｒ曲线基因表达，构造了用于优化设计的适应度函数，发展了一种小种群演化方法。针对小种群基因算法中出现的近亲繁殖问题，提出了远亲配对策略、构造了自适应非均匀变异算子，提高了算法的收敛速度。文中最后给出了基于全位势方程求解程序的翼型重构反设计以及单目标和多目标翼型优化算例。

Genetic Algorithms with Application to Multi-objective Optimization of Aerodynamic Shapes

In this paper, Genetic Algorithms (GAs) is applied to the optimization of aerodynamic design problems. The Bezier Curve is used for shape representation of the aerodynamic shapes.In the implementation of GAs, the fitness function is defined based on the features of the optimization problem and an evolution method with small population size is developed. The strategies of distant relatives to mate and adaptive mutation operator are presented based on the genetic distance for the consideration of inbreeding problem of GAs with small size of population. The numerical results for multiple objective optimization of maximizing the lift drag ratio of the airfoils are obtained based on the solver of the potential equation.