CDV-Transport Research Centre, Brno, Czech Republic.
Faculty of Science, Palacký University, Olomouc, Czech Republic.
PLoS One. 2019 Jul 17;14(7):e0219658. doi: 10.1371/journal.pone.0219658. eCollection 2019.
We introduce a rapid deterministic algorithm for identification of the most critical links which are capable of causing network disruptions. The algorithm is based on searching for the shortest cycles in the network and provides a significant time improvement compared with a common brute-force algorithm which scans the entire network. We used a simple measure, based on standard deviation, as a vulnerability measure. It takes into account the importance of nodes in particular network components. We demonstrate this approach on a real network with 734 nodes and 990 links. We found the worst scenarios for the cases with and without people living in the nodes. The evaluation of all network breakups can provide transportation planners and administrators with plenty of data for further statistical analyses. The presented approach provides an alternative approach to the recent research assessing the impacts of simultaneous interruptions of multiple links.
我们引入了一种快速确定性算法，用于识别最关键的链路，这些链路能够导致网络中断。该算法基于在网络中搜索最短循环，并与扫描整个网络的常见暴力算法相比提供了显著的时间改进。我们使用了一种简单的基于标准偏差的度量作为脆弱性度量，它考虑了节点在特定网络组件中的重要性。我们在一个具有 734 个节点和 990 个链路的真实网络上演示了这种方法。我们找到了有和没有人居住在节点情况下的最坏情况。对所有网络中断的评估可以为交通规划者和管理员提供大量数据，以进行进一步的统计分析。所提出的方法为最近研究评估多个链路同时中断的影响提供了另一种方法。
