Stochastic Block Models as a Modeling Approach for Dynamic Material Flow Networks in Manufacturing and Logistics

Stochastic Block Models as a Modeling Approach for Dynamic Material Flow Networks in Manufacturing and Logistics
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随机块模型作为制造和物流中动态物料流网络的建模方法

DOI:
10.1016/j.procir.2018.03.209
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发表时间:
2018
期刊:
Procedia CIRP
影响因子:
--
通讯作者:
T. Becker
T. Becker
中科院分区:
--
文献类型:
--
作者:
T. Becker

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物流和制造业中的物流流程产生了大量的数据,这些数据是由代理、资源和信息的相互作用引起的。此外,高度互连的材料流形成网络状结构。但目前很多分析和预测工具仍然忽略了数据的网络类来源。因此,需要进一步的建模方法,其中也包括数据的网络结构。这种方法是将随机块模型与物质流的网络表示相结合,用迭代算法推断内部组结构。
Material flow processes in logistics and manufacturing generate enormous amounts of data, induced by the interplay of agents, resources, and information. Furthermore, the highly interconnected material flow forms a network-shaped structure. But still a lot of analysis and forecasting tools neglect the network alike origin of the data. Therefore, further modeling approaches which also include the network structure of the data are needed. Such an approach is the combination of the stochastic block model with the network representation of the material flow, which infers the internal group structure with an iterative algorithm.
DOI: --
发表时间: 2016
期刊:
影响因子: --
作者:
D. Wagner;T. Becker
通讯作者: T. Becker
DOI: 10.1103/physreve.80.056117
发表时间: 2009-11-01
期刊: PHYSICAL REVIEW E
影响因子: 2.4
作者:
Lancichinetti, Andrea;Fortunato, Santo
通讯作者: Fortunato, Santo