基于神经网络和遗传算法的塑料热压成型多目标优化

论述了人工神经网络和遗传算法在塑料热压成型工艺优化中的应用,首先利用人工神经网络建立热压成型工艺参数与零件性能之间关系的数学模型,然后用遗传算法对工艺参数优化。根据多目标函数优化问题的单目标化思想,对优化后的单目标进行分解,得到最优工艺参数条件下的塑料热压产品性能,从而为建立和控制塑料热压成型工艺参数提供了一种行之有效的方法。

Multiobjective Optimization of Plastic Thermoforming based on Neural Network and Genetic Algorithm

The application of artificial neural network and genetic algorithm for processing optimization of plastic thermoforming was discussed.First of all,the mathematics model between the process parameters for plastic thermoforming and the property of the part was set up with neural network.Then,the process parameters was optimized with genetic algorithm.According to the idea of converting the multiobjective optimization problem into the single-objective one,the optimal single-objective was decomposed and the property of the part on the optimal condition was obtained.So,it was a kind of effectual means for setting up and controlling parameters of plastic thermoforming.