近似技术在遗传算法和结构优化设计中的应用

在传统结构优化设计中．基于近似技术和灵敏度分析的结构重分析技术可以显降低结构有限元分析的次数。本提出了一套适于遗传算法应用的近似模型——分段近似模型。该分段近似模型可以极大地降低结构有限元分析的次数，并且可以提高遗传算法的收敛性，从而提高遗传算法的计算效率。本通过两个实例验证了该分段近似模型的有效性。

APPROXIMATION TECHNIQUES FOR APPLICATION OF GENETIC ALGORITHMS TO STRUCTURAL OPTIMIZATION

Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.