遗传算法作为一种比较成熟的智能算法,因其具有全局搜索能力和并行性得以在翼型气动优化中广范应用。本文在编码方式、种群初始化和遗传算子等方面对标准遗传算法进行了改进。其中,DNA的编码方式增加信息的丰富性;拉丁超立方抽样初始化使种群分布相对均匀;插入、删除、倒位等算子增加种群的多样性,加快收敛;感染算子加速种群摆脱停滞或早熟。计算结果表明:与标准遗传算法相比,改进后的DNA编码遗传算法收敛更快,全局性更好。 Genetic algorithm as a more mature intelligent algorithm, because of its global search capabilities and parallelism can be widely used in aerodynamic optimization of airfoils. In this paper, the standard genetic algorithm is improved in coding, population initialization and genetic operators. Among them, the encoding of DNA increased the richness of information; Initialization of Latin hypercube sampling made population distribution relatively uniform; Insertion, deletion, inversion and other operators increased the diversity of populations and accelerated convergence; infection operators accelerated the population to get rid of stagnation or precocious puberty . The results show that compared with the standard genetic algorithm, the improved DNA coding genetic algorithm converges faster and the overall situation is better.