混合遗传算法及其在翼型气动多目标优化设计中的应用

Hybrid genetic algorithm and its application in multi-objective aerodynamic optimization design of airfoil

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。

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.