中文摘要：

针对目前飞行器优化设计领域遗传算法计算量大、效率低的情况。提出了基于连续空间蚊群算法的高超声速飞行器气动布局优化设计方法。蚁群算法是近年来发展的一种全新仿生算法，具有全局性和高效性等特点．已经成功地应用于离散空间的优化设计。采用连续空间蚁群算法，对高超声速飞行器进行了多变量、多约束下的气动布局优化设计，并与采用遗传算法和约束可变多面体法的优化结果进行了对比，指出了蚁群算法的优点。本文的研究可为蚁群算法应用于复杂、高维的大规模飞行器设计问题提供参考。

英文摘要：

Aimed at the great computed cost and low efficiency of Genetic Algorithm （GA） in the optimization design field of aircraft, a new optimization design method of aerodynamic configuration for hypersonic cruise vehicle （HCV） based on ant colony algorithm （ACA） in continuous space is presented. ACA is a new bionic optimization algorithm developed in recent years, and with global and efficient characteristics, it has been applied in discontinuous space. Using ACA in continuous space, this paper periorms a multi-variable and multi-restrained optimization work of aerodynamic configuration for HCV. And through the eomparison with GA and Constrained Flexible Polyhedrow Method （CFPM）, ACA shows its advantages. Finally, from this research work, ACA has great referenced values to complex, multidimensional and large-scale optimization problems in aircraft design field.