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本文在确定FMS动态调度的优化目标和策略的前提下,提出了基于规则的反向传播学习算法(BP)的神经网络FMS动态调度的方法,FMS的生产状态参数作为神经网络的输入,动态调度策略作为网络的输出。通过实例验证本文提出FMS动态调度的方法简单性、灵活性和实时性等特点。
In this paper, the FMS dynamic scheduling algorithm based on the rule-based backpropagation learning algorithm (BP) is proposed on the premise of determining the optimization goals and strategies of the FMS dynamic scheduling. The production status parameters of the FMS are used as the input of the neural network and the dynamic scheduling Strategy as the output of the network. The example verifies that the method of FMS dynamic scheduling is simple, flexible and real-time.