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Empirical topological investigation of practical supply chains based on comlplex networks

机译:基于复杂网络的实际供应链的经验拓扑研究

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摘要

The industrial supply chain networks basically capture the circulation of social resource,dominating the stability and efficiency of the industrial system.In this paper,we provide an empirical study of the topology of smartphone supply chain network.The supply chain network is constructed using open online data.Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution,in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost.We also detect the community structure to find the basic functional unit.It shows that information communication between nodes is crucial to improve the resource utilization.We should pay attention to the global resource configuration for such electronic production management.
机译:工业供应链网络基本上捕获了社会资源的流通,支配着工业系统的稳定性和效率。本文对智能手机供应链网络的拓扑结构进行了实证研究。实验结果表明,智能手机供应链网络具有小规模,无标度分布的特点,其中几个高级节点对该功能起着关键作用,可以有效降低通信成本。社区结构找到基本的功能单元。这表明节点之间的信息通信对于提高资源利用率至关重要。对于此类电子生产管理,我们应注意全局资源配置。

著录项

  • 来源
    《中国物理:英文版》 |2017年第11期|144-150|共7页
  • 作者单位

    National Engineering Laboratory for Big Data Computing Systems, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;

    National Engineering Laboratory for Big Data Computing Systems, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;

    National Engineering Laboratory for Big Data Computing Systems, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;

    Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417, Singapore;

    National Engineering Laboratory for Big Data Computing Systems, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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