基于动态阈值神经网络模型的多功能机床Flow Shop排序研究

在生产作用排序中若能充分利用机床功能多样性这一特点，就可有效地缩短零件的总加工时间，提高机床利用率，并使加工系统更具动态应变能力，但机床功能的曾多也使使用排序问题的求解更加复杂和困难，为了降低求解模型的复杂性，这里提出了一种基于动态阈值的神经网络模型与动态调度规则相结合的方法，有于求解面向多功能机床的Flow Shop排序问题。数值实验结果表明了文中方法的有效性。

scheduling now shop for multi-function machine tools based on the ANN model with dynamic threshold

Making full use of different functions of a machine tool during manufacturing can effectively shorten the processing time of parts. And then idle time of the machine tools can be decreased and the dynamic ability of the processing systems to the sudden changes can be enhanced. However, the consideration of multi- functional machine tools would also complicate the scheduling problems. In order to lessen the complexity a method based on the combination of the ANN model and the dynamic dispatching rules is suggested in this paper, which can be applied in scheduling flow shop problem for multi-function machine tools. A number of digital experiments are conducted to show the validity of this method