Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm
We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulner...
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Hindawi Limited
2014-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/356963 |
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doaj-0a472722c5e24156ae61202cb5a43ca22020-11-24T22:41:38ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/356963356963Road Network Vulnerability Analysis Based on Improved Ant Colony AlgorithmYunpeng Wang0Yuqin Feng1Wenxiang Li2William Case Fulcher3Li Zhang4School of Transportation Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Transportation Science and Engineering, Beihang University, Beijing 100191, ChinaKey Laboratory of Road Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, ChinaDepartment of Civil and Environmental Engineering, Mississippi State University, Starkville, MS 39759, USADepartment of Civil and Environmental Engineering, Mississippi State University, Starkville, MS 39759, USAWe present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.http://dx.doi.org/10.1155/2014/356963 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yunpeng Wang Yuqin Feng Wenxiang Li William Case Fulcher Li Zhang |
spellingShingle |
Yunpeng Wang Yuqin Feng Wenxiang Li William Case Fulcher Li Zhang Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm Mathematical Problems in Engineering |
author_facet |
Yunpeng Wang Yuqin Feng Wenxiang Li William Case Fulcher Li Zhang |
author_sort |
Yunpeng Wang |
title |
Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm |
title_short |
Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm |
title_full |
Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm |
title_fullStr |
Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm |
title_full_unstemmed |
Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm |
title_sort |
road network vulnerability analysis based on improved ant colony algorithm |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2014-01-01 |
description |
We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management. |
url |
http://dx.doi.org/10.1155/2014/356963 |
work_keys_str_mv |
AT yunpengwang roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm AT yuqinfeng roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm AT wenxiangli roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm AT williamcasefulcher roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm AT lizhang roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm |
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1725701456225370112 |