Abstract: 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 process parameters were obtained. By comparing and verification, this multi-objective optimization method can improve multiple quality indicators in the case of lacking sufficient orthogonal data.

Key words: multi-objective optimization, injection molding, processing parameter, neural networks ensemble, agent model, genetic algorithm