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

Abstract

MOEA/D-DE algorithm is easy to implement and widely used to deal with multi-objective optimization problems, while its hyper-parameters 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 in the differential evolution operator, and the Levy flight strategy is used to control the scale factor. Then the hyper-parameters in the MOEA/D-DE algorithm obtain adaptive ability. And MOEA/DDE 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 aero-dynamic stealth optimization of airfoil. The function test results show that the new algorithm has good perfor-mance, 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 algo-rithms.

Keywords

• multi-objective optimization algorithm
• multiobjective evolutionary algorithm based on decomposition(moea/d)
• hyper-parameters
• sensitivity analysis
• aerodynamic stealth optimization
• differential evolution operator