超参数自适应的MOEA/D-DE算法在翼型气动隐身优化中的应用

MOEA/D-DE 算法易于实现，被广泛应用于处理多目标优化问题，但其超参数CR 和F 对算法性能影响较大。基于MOEA/D-DE 算法框架、利用Sobol 全局灵敏性分析方法对差分进化算子中的交叉控制参数CR进行改进，使用莱维飞行策略控制比例因子F，使算法中的超参数拥有自适应能力，得到超参数自适应的MOEA/D-DE 算法——MOEA/D-DEAH 算法；对MOEA/D-DEAH 算法、不同超参数设置的MOEA/D-DE算法和NSGAII 算法进行函数测试和翼型气动隐身优化算例对比。结果表明：MOEA/D-DEAH 算法性能良好，具有较强的鲁棒性，气动隐身优化效果也比其他算法更好。

Application of hyper-parameters adaptive MOEA / D-DE algorithm in aerodynamic stealth optimization of airfoil

MOEA/D-DE algorithm is easy to implement and widely used to deal with multi-objective optimization problems, while its hyper-parameters CR and F have a great impact on the performance of the algorithm. In this paper, based on the MOEA/D-DE algorithm framework, the Sobol global sensitivity analysis method is used to improve the cross control parameter CR in the differential evolution operator, and the Levy flight strategy is used to control the scale factor F. Then the hyper-parameters in the MOEA/D-DE algorithm obtain adaptive ability. And MOEA/D-DE algorithm with adaptive hyper-parameters (MOEA/D-DEAH) is proposed. The MOEA/D-DEAH MOEA/D-DE with different hyper-parameters settings and NSGAII are tested and compared with function tests and aerodynamic stealth optimization of airfoil. The function test results show that the new algorithm has good performance, and the algorithm can obtain strong robustness by adapting the super parameters. The optimization results of airfoil aerodynamic stealth show that MOEA/D-DEAH algorithm has better optimization results than other algorithms.