气动优化设计中的紧凑混合遗传算法  

A Compact Hybrid Genetic Algorithm in Aerodynamic Optimization Design

作　　者：王晓鹏[1] 

机构地区：[1]西北工业大学

出　　处：《弹箭与制导学报》2003年第1期65-68,共4页Journal of Projectiles,Rockets,Missiles and Guidance

摘　　要：与传统的梯度法相比,遗传算法的缺点在于计算过多的目标函数适应值而增加了优化设计的计算量。为了提高遗传算法的优化效率,把传统的梯度法与遗传算法相结合,建立了气动优化设计中的紧凑混合遗传算法(CHGA)。该算法将梯度法作为遗传算法中的一个遗传算子加入到遗传算法中,在保持遗传算法原有良好的全局性等优点的前提下改善算法的效率。应用混合遗传算法进行跨音速翼型的反设计和波阻优化设计,并与采用优选策略的标准遗传算法的设计结果进行比较。结果表明混合遗传算法能有效的提高气动优化设计的效率。Genetic algorithm, compared with some conventional gradientbased methods, when applied to optimization design, has a primary disadvantage that computational cost increases greatly for overmuch evaluation of objective functions and their fitness. To improve efficiency of optimization by means of genetic algorithms, a compact hybrid genetic algorithm (CHGA) in aerodynamic optimization design is constructed by combining a conventional gradientbased method with the commonused genetic algorithm. Gradientbased method, taken as a genetic operator, is embedded into genetic algorithm to form hybrid genetic algorithm to improve efficiency of algorithm keeping perfectly global property. As application, hybrid genetic algorithm is used to carry out inverse design and wave optimization design of transonic airfoils. Compared with the results using standard genetic algorithm adopting elitist strategy, hybrid genetic algorithm is considered to be more efficient when applied in aerodynamic optimization design.

关 键 词：气动优化设计 紧凑混合遗传算法 跨音速翼型 梯度算法 标准遗传算法 

分 类 号：V224[航空宇航科学与技术—飞行器设计] V221.3