In this paper, an approach for resource constrained FMS scheduling is described, which integrates Hopfield neural network and simulated annealing algorithm.
提出利用神经网络和模拟退火技术来求解有约束的FMS资源调度问题的一种新方法。
It is analyzed from three levels of knowledge acquirement, representation and inference, and the object-oriented representation of knowledge in FMS scheduling domain is mainly introduced.
本文从知识获取、表示和推理三个方面进行了论述，重点介绍了FMS调度领域专家知识的面向对象表示。
The algorithm provides a chance to simplify FMS dynamic scheduling and improve system productivity.
此算法为简化fms的动态调度和提高系统生产率创造了条件。
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