Forecasting Changes in Material Flow Networks with Stochastic Block Models
Forecasting Changes in Material Flow Networks with Stochastic Block Models
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DOI：
10.1016/j.procir.2019.03.289
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Thorben Funke;T. Becker
中科院分区：
文献类型：
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作者：
Thorben Funke;T. Becker
物流和制造业的物流变得越来越动态和灵活，与此同时，这些系统随着货物和合作伙伴数量的增加而增长。现有的预测解决方案需要详细的信息来创建关于系统未来状态的适当预测。因此，我们提出了一种使用随机区块模型(SBM)的新方法，该方法只需要将所考虑的系统聚集表示为物质流网络。基于对所调查的物流网络的推断聚类，我们能够预测特定路径和整个系统的使用。
Material flows in logistics and manufacturing become increasingly dynamic and flexible and at the same time those systems grow with increasing number of goods and partners. Existing forecasting solutions require detailed information to create an appropriate prediction about future states of the system. Therefore, we propose a new approach using the Stochastic Block Model (SBM), which needs only the aggregated representation of the considered system as a material flow network. Based on an inferred clustering of the investigated material flow network, we are able to predict the usage of specific paths and the system as a whole.