北京航空航天大学学报 ›› 2006, Vol. 32 ›› Issue (05): 508-512.

• 论文 • 上一篇    下一篇

设计敏度在气动弹性遗传优化中的应用

万志强, 杨超   

  1. 北京航空航天大学 航空科学与工程学院, 北京 100083
  • 收稿日期:2005-06-03 出版日期:2006-05-31 发布日期:2010-09-20
  • 作者简介:万志强(1976-),男,江西南昌人,博士后, wzq@buaa.edu.cn.
  • 基金资助:

    国家自然科学基金资助项目(10502003,10372013);航空科学基金资助项目(03A51050)

Application of design sensitivity in aeroelastic genetic optimization

Wan Zhiqiang, Yang Chao   

  1. School of Aeronautic Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2005-06-03 Online:2006-05-31 Published:2010-09-20

摘要: 利用遗传算法和遗传/敏度混合优化算法对某复合材料机翼进行气动弹性优化设计研究,并提出在使用这两种算法时根据设计敏度信息计算设计变量的重要性指标、从而确定主要和次要设计变量、进而调整设计变量变化域的方法,以提高算法的寻优效率.研究表明:设计变量变化域的定义直接影响遗传算法和遗传/敏度混合优化算法的寻优效率,特别是单独使用遗传算法时影响程度更大;定义时应该在确保设计空间包含足够的优秀可行解的前提下,尽可能地缩减搜索空间.所提出的基于设计敏度调整设计变量变化域的方法在实际应用中能取得较好的效果:该方法既能明显提高遗传算法和遗传/敏度混合优化算法的搜索效率,又能显著增强两种算法辨识可行域的能力.

Abstract: A design study aimed to optimize a composite wing in an aeroelastic way was presented using genetic algorithm and genetic/sensitivity-based hybridalgorithm. In order to increase the search efficiency of the above-mentioned two algorithms, a set of methods was put forward to fix primary and secondary design variables followed by adjusting the design variable domain on the basis of design variable importance in terms of their sensitivity. Results demonstrate that the size of design variable domain had direct effects on the search efficiency of genetic algorithm and genetic/sensitivity-based hybrid algorithm, especially when the former was used. Therefore, the search space should be reduced to be as small as possible if an enough amount of excellent feasible solutions in design space could be ensured. Results indicate that the method to adjust the size of design variable domain on the basis of sensitivity has proved to be of fairly practical success, which can not only remarkably increase the search efficiency of genetic algorithm and genetic/sensitivity-based algorithm, but also strengthen the capability of the two algorithms to discriminate the feasible field.

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