本世纪80年代以来,神经网络(NN)的研究引起了许多领域的重视。这种由大量简单神经元经广泛连接构成的一种计算结构,在工程上有巨大的应用潜力。 本文用Hopfield神经网络求解Job-shop类作业排序问题。在本文中,将依据实际生产过程中对整个生产作业计划的各种约束条件,给出相应的数学模型。其中,以按时交货为作业计划的优化目标,给出相应的数学推导和参数选择之间的基本关系;最后,给出一些实际运算的仿真结果。这些数据将证明本文中所采用的建模方法,不仅适用于静态调度问题,也适用于动态调度,效果是令人满意的。 Since the 1980s, the research of neural network (NN) has drawn much attention in many fields. This kind of computing structure consisting of a large number of simple neurons extensively connected has great potential in engineering. This paper uses Hopfield neural network to solve Job-shop class scheduling problem. In this paper, the corresponding mathematical model will be given based on the various constraints planned for the entire production operation in the actual production process. Among them, on-time delivery is the optimization objective of job plan, and the basic relationship between mathematical derivation and parameter selection is given. Finally, some simulation results of actual operation are given. These data will prove that the modeling method adopted in this paper not only applies to the static scheduling problem, but also to the dynamic scheduling, the effect is satisfactory.