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构造了一种新型基于基因算法与博弈论的并行分级多目标优化方法,并应用于多段翼型气动反设计。此方法基于二进制编码的基因算法和博弈论,优化变量被分配给不同的博弈者,因而总体优化问题转变为分裂空间中的局部优化问题。文中给出了一个多段翼型形状/位置可压位流的反设计问题的求解算例,引入了基于非结构网格的分级结构。与传统基因算法数值算例的对比表明了本文构造的并行分级算法具有较高的计算效率,可广泛应用于多目标优化问题。
A new parallel hierarchical multi-objective optimization method based on genetic algorithm and game theory is constructed and applied to multi-segment airfoil inverse design. This method is based on the genetic algorithm and game theory of binary coding, and the optimization variables are assigned to different gamers. Therefore, the overall optimization problem is transformed into a local optimization problem in split space. In this paper, an example of solving the inverse design problem of multi-section airfoil shape / position compressible flow is given, and a hierarchical structure based on unstructured grid is introduced. Compared with the traditional numerical examples of genetic algorithms, it shows that the parallel hierarchical algorithm constructed in this paper has high computational efficiency and can be widely used in multi-objective optimization problems.