中文摘要：

以计算机辅助工程（CAE）数值仿真正交试验所得工艺参数与质量指标的数据作为训练样本，对经过优化的BP神经网络进行训练，得到工艺参数与制品质量指标之间的神经网络集近似计算代理模型，该模型快速准确，有明确的数学公式，可以利用遗传算法进行全局寻优，得到使多个质量指标综合最优的工艺参数组合。通过对比验证，这种多目标优化方法可以在正交试验结果数据较少的情况下较大程度地提高制品的多个质量指标。

英文摘要：

The data from CAE simulation orthogonal test was used as training samples to establish the neural networks ensemble approximate calculation agent model. With clear mathematical formula, the model may carry out global optimization by genetic algorithm quickly and accurately, and the optimal processing parameters were obtained. By comparison and verification, this multiobjective optimization method could improve multiple quality indicators in the case of lacking sufficient orthogonal data.