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混合遗传算法及其在翼型气动多目标优化设计中的应用
引用本文:王晓鹏.混合遗传算法及其在翼型气动多目标优化设计中的应用[J].空气动力学学报,2001,19(3):256-261.
作者姓名:王晓鹏
作者单位:西北工业大学
摘    要:把基于实数编码的自适应遗传算法(SAGA)与可变容差法相结合,建立了数值优化设计中的混合遗传算法(HGA),并将其与翼型的气动分析相结合进行跨声速翼型的单目标和多目标气动优化设计。与自适应遗传算法相比,混合遗传算法的优化质量略有改善,优化效率有明显的提高。优化结果表明混合遗传算法在翼型单目标和多目标气动优化设计中是十分有效的。

关 键 词:混合遗传算法  跨声速翼型  气动优化设计  随机性优化方法  HGA  单目标气动优化设计  多目标气动优化设计  自适应遗传算法  SAGA
文章编号:0258-1825(2001)03-0256-06
修稿时间:2000年10月25

Hybrid genetic algorithm and its application in multi-objective aerodynamic optimization design of airfoil
WANG Xiao,peng.Hybrid genetic algorithm and its application in multi-objective aerodynamic optimization design of airfoil[J].Acta Aerodynamica Sinica,2001,19(3):256-261.
Authors:WANG Xiao  peng
Abstract:One of the hybrid genetic algorithms in numerical optimization design has been established by combining self adaptive genetic algorithm based on real number encoding skill with variable tolerance method. Then the algorithm, combined with aerodynamic analysis of airfoil, is used to carry out aerodynamic optimization design of transonic airfoil with single objective and multiple objectives. Compared with self adaptive genetic algorithm, the hybrid genetic algorithm has much higher computation efficiency and a little higher quality. The results have shown that hybrid genetic algorithm is effective and efficient to deal with aerodynamic optimization design of airfoil with single and multiple objectives.
Keywords:hybrid genetic algorithm  transonic airfoil  aerodynamic optimization design
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