基于Pareto遗传算法的复合材料机翼优化设计

Optimization for composite wing based on Pareto genetic algorithm

针对某型飞机设计过程中遇到的副翼反效问题,提出了复合材料机翼满足气动弹性要求的优化方法,构造了一种基于Pareto最优解定义的多目标遗传算法——Pareto遗传算法.该算法以权重信息为基础建立Pareto解集过滤器,引入小生境技术等实现Pareto前沿面的求解.测试函数计算表明该算法有较好的收敛性.以复合材料机翼的升力系数和滚转力矩系数为目标函数,采用Pareto遗传算法进行计算得出一组Pareto最优解集,计算结果表明,给出的方案能够满足工程需求,为决策者提供了多种可选方案.

To solve the aileron reversal problem in aircraft design, an aero-elastic tailoring optimization model of composite wing for engineering requirement was established and the Pareto genetic algorithm （PGA） based on Pareto optimal set was developed. In order to obtain the Pareto optimal set, the Pareto filtering pool was constructed based on weight information in PGA. And the niche technology was utilized to keep the diversity of population. The computation of the test function indicates that PGA has good convergence. In the numerical example, setting the lifting coefficient and the rolling moment coefficient as objective functions, the expected Pareto optimal set was obtained by using PGA. The results show that the Pareto optimal set satisfies the engineering requirement and can provide many feasible projects for the decision-maker to choose.