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在气动优化设计中,发展一些计算代价小同时又具有较好的全局/局部搜索平衡能力的优化算法十分重要。针对此,文章提出了一种基于膜概念和Kriging模型的混合优化算法。该算法对细胞膜的结构和新陈代谢运作机制进行了仿真,将粒子群优化算法与差分进化算法有机地结合了起来,增强了算法的寻优能力,同时,引入Kriging模型进行预估寻优,极大地减少了计算开销。函数测试结果表明,该混合算法具有很好的寻优能力。将该算法应用到单段翼翼型和两段翼翼型的设计之中,取得了良好的结果。
In the aerodynamic optimization design, it is very important to develop some optimization algorithms with small computational cost and good global / local search equilibrium. In view of this, the paper presents a hybrid optimization algorithm based on the membrane concept and the Kriging model. This algorithm simulates the structure of cell membrane and the mechanism of metabolism, and combines particle swarm optimization algorithm with differential evolution algorithm to enhance the optimization ability of the algorithm. At the same time, the Kriging model is introduced to estimate the optimal solution. Reduce the calculation overhead. Function test results show that the hybrid algorithm has a good search ability. The algorithm is applied to the design of single wing airfoil and two wing airfoils with good results.