航空学报 > 2002, Vol. 23 Issue (2): 177-179

Pareto基因算法多目标翼型优化设计

隋洪涛, 陈红全, 黄明恪   

  1. 南京航空航天大学601教研室 江苏南京 210016
  • 收稿日期:2001-04-19 修回日期:2001-10-23 出版日期:2002-04-25 发布日期:2002-04-25

MULTI-OBJECTIVE AIRFOIL OPTIMIZATION USING PARETO GENETIC ALGORITHM

SUI Hong-tao, CHEN Hong-quan, HUANG Ming-ke   

  1. Faculty 601, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2001-04-19 Revised:2001-10-23 Online:2002-04-25 Published:2002-04-25

摘要:

基于 Pareto最优解的定义,通过构造新型的联赛式选择复制等算子而发展了一种适合于求解多目标优化设计的 Pareto基因算法。通过等级法来正确识别每一代中近 Pareto波阵面的解,从而消除选择误差达到快速收敛的目的。为提高解的分布性:采用小生境技术解决了基因材料多样性损失问题;采用常规实数编码方式配合平均交叉算子解决了编码端点效应问题。将所发展的方法应用于多目标翼型优化设计中,获得了理想的 Pareto波阵面,为决策者提供了一个可选的有效解数据库。

关键词: 基因算法, Pareto最优解, 多目标优化设计, 翼型

Abstract:

Based on the definition of Pareto optimum, a Pareto Genetic Algorithm (PGA) suitable for multi objective optimization is developed using a set of operators and strategies in this paper. The search process of the PGA is speeded up by presenting a ranking method. The distribution of the solutions on the Pareto front is improved from two angles. Firstly, the niching technology is used to keep the genetic diversity. Secondly, the real coding combined with an average crossover operator is used to eliminate the ending effect of the GA coding. Then the constructed PGA is used to solve the multi objective airfoil optimization problem. And the satisfying Pareto front is obtained.

Key words: genetic algorithm, Pareto optimum, multi-objective optimization, airfoil