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A deterministic approach for rapid identification of the critical links in networks
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 algor...
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Published in: | PloS one 2019-07, Vol.14 (7), p.e0219658-e0219658 |
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description | 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. |
doi_str_mv | 10.1371/journal.pone.0219658 |
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0219658</identifier><identifier>PMID: 31314814</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Computer and Information Sciences ; Czech Republic ; Data Collection ; Deterministic models ; Engineering and Technology ; Humans ; Identification ; Links ; Medicine and Health Sciences ; Modern culture ; Monte Carlo simulation ; Nodes ; Physical Sciences ; Probability ; Records ; Research and Analysis Methods ; Social Sciences ; Software ; Statistical analysis ; Statistical analysis of data ; Time ; Transportation</subject><ispartof>PloS one, 2019-07, Vol.14 (7), p.e0219658-e0219658</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Vodák et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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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.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Computer and Information Sciences</subject><subject>Czech Republic</subject><subject>Data Collection</subject><subject>Deterministic models</subject><subject>Engineering and Technology</subject><subject>Humans</subject><subject>Identification</subject><subject>Links</subject><subject>Medicine and Health Sciences</subject><subject>Modern culture</subject><subject>Monte Carlo simulation</subject><subject>Nodes</subject><subject>Physical Sciences</subject><subject>Probability</subject><subject>Records</subject><subject>Research and Analysis Methods</subject><subject>Social Sciences</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Statistical analysis of 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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. 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subjects | Algorithms Analysis Computer and Information Sciences Czech Republic Data Collection Deterministic models Engineering and Technology Humans Identification Links Medicine and Health Sciences Modern culture Monte Carlo simulation Nodes Physical Sciences Probability Records Research and Analysis Methods Social Sciences Software Statistical analysis Statistical analysis of data Time Transportation |
title | A deterministic approach for rapid identification of the critical links in networks |
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