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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Main Authors: Yunpeng Wang, Yuqin Feng, Wenxiang Li, William Case Fulcher, Li Zhang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/356963
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spelling 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
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AT yuqinfeng roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm
AT wenxiangli roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm
AT williamcasefulcher roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm
AT lizhang roadnetworkvulnerabilityanalysisbasedonimprovedantcolonyalgorithm
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