中文摘要：

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Kfiging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。

英文摘要：

We propose what we believe to be a new and better algorithm which we call HMCK algorithm that has both good global search ability and good local search ability but has lower computational cost for aerodynamic optimization. Sections 1,2and 3 explain our HMCK algorithm; their core consists of： （ 1 ） we simulate the structure of cell membrane and its mechanism of metabolism and combine the particle swarm optimization （PSO） algorithm with the differential evolution （DE） algorithm, thus enhancing the optimization efficiency; （2） we introduce the Kriging model into our HMCK algorithm in order for it to have some prediction and optimization ability and reduce its com- putational cost. Section 4 performs the function test of our HMCK algorithm; the function test results, given in Tables 1 and 2, show preliminarily that our HMCK algorithm has much better optimization ability than the PSO algorithm and the DE algorithm. Section 5 applies our HMCK algorithm to the design of single-section airfoil and the double-section airfoil respectively; the design results, presented in Figs. 3 through 6, show preliminarily that our HMCK algorithm does have better optimization efficiency.