Robustness of the air transport network

•This paper defines a methodology to detect critical airports of the air transport network (ATN).•The methodology is based on the effect of airport disconnection on size of giant component.•A list of critical airports for the global ATN of November 2011–November 2012 is presented.•A new node selecti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2014-08, Vol.68, p.155-163
Hauptverfasser: Lordan, Oriol, Sallan, Jose M., Simo, Pep, Gonzalez-Prieto, David
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 163
container_issue
container_start_page 155
container_title Transportation research. Part E, Logistics and transportation review
container_volume 68
creator Lordan, Oriol
Sallan, Jose M.
Simo, Pep
Gonzalez-Prieto, David
description •This paper defines a methodology to detect critical airports of the air transport network (ATN).•The methodology is based on the effect of airport disconnection on size of giant component.•A list of critical airports for the global ATN of November 2011–November 2012 is presented.•A new node selection criterion to disconnect airports presented, based on Bonacich power centrality.•This new criterion is compared to a wide range of node selection criteria present in the literature. This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.
doi_str_mv 10.1016/j.tre.2014.05.011
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1642273082</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1366554514000805</els_id><sourcerecordid>1642273082</sourcerecordid><originalsourceid>FETCH-LOGICAL-c422t-36d5e84ceaee305d896fca2722bedde6a0bc39b38d050e6641fec2ccf1fe45113</originalsourceid><addsrcrecordid>eNp9kM1LxDAQxYMouK7-Ad4KHvTSOvlsiydZ_IIFQfQc0nSKrbvNmqSK_71Z15MHT28Ovzfz5hFySqGgQNXlUESPBQMqCpAFULpHZrQqq1yWtdhPM1cql1LIQ3IUwgCQTJLNyPmTa6YQRwwhc10WXzEzvc-iN2PYOB-zEeOn82_H5KAzq4AnvzonL7c3z4v7fPl497C4XuZWMBZzrlqJlbBoEDnItqpVZw0rGWuwbVEZaCyvG161IAGVErRDy6ztkgpJKZ-Ti93ejXfvE4ao132wuFqZEd0UNFXpTsmhYgk9-4MObvJjSqepFEqWsmYiUXRHWe9C8Njpje_Xxn9pCnpbnR50qk5vq9MgNfyEuNp5MH360aPXwfY4Wmx7jzbq1vX_uL8BRv51yA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1546575924</pqid></control><display><type>article</type><title>Robustness of the air transport network</title><source>Elsevier ScienceDirect Journals</source><creator>Lordan, Oriol ; Sallan, Jose M. ; Simo, Pep ; Gonzalez-Prieto, David</creator><creatorcontrib>Lordan, Oriol ; Sallan, Jose M. ; Simo, Pep ; Gonzalez-Prieto, David</creatorcontrib><description>•This paper defines a methodology to detect critical airports of the air transport network (ATN).•The methodology is based on the effect of airport disconnection on size of giant component.•A list of critical airports for the global ATN of November 2011–November 2012 is presented.•A new node selection criterion to disconnect airports presented, based on Bonacich power centrality.•This new criterion is compared to a wide range of node selection criteria present in the literature. This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.</description><identifier>ISSN: 1366-5545</identifier><identifier>EISSN: 1878-5794</identifier><identifier>DOI: 10.1016/j.tre.2014.05.011</identifier><identifier>CODEN: TRERFW</identifier><language>eng</language><publisher>Exeter: Elsevier India Pvt Ltd</publisher><subject>Air transport ; Air transport network ; Air transportation industry ; Airport closure ; Airports ; ATN ; Complex networks ; Computer networks ; Computer simulation ; Connectivity ; Contingency planning ; Contingency plans ; Criteria ; Intentional attacks ; Networks ; Robustness ; Shutdowns ; Studies ; Transportation</subject><ispartof>Transportation research. Part E, Logistics and transportation review, 2014-08, Vol.68, p.155-163</ispartof><rights>2014 Elsevier Ltd</rights><rights>Copyright Elsevier Sequoia S.A. Aug 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-36d5e84ceaee305d896fca2722bedde6a0bc39b38d050e6641fec2ccf1fe45113</citedby><cites>FETCH-LOGICAL-c422t-36d5e84ceaee305d896fca2722bedde6a0bc39b38d050e6641fec2ccf1fe45113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.tre.2014.05.011$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids></links><search><creatorcontrib>Lordan, Oriol</creatorcontrib><creatorcontrib>Sallan, Jose M.</creatorcontrib><creatorcontrib>Simo, Pep</creatorcontrib><creatorcontrib>Gonzalez-Prieto, David</creatorcontrib><title>Robustness of the air transport network</title><title>Transportation research. Part E, Logistics and transportation review</title><description>•This paper defines a methodology to detect critical airports of the air transport network (ATN).•The methodology is based on the effect of airport disconnection on size of giant component.•A list of critical airports for the global ATN of November 2011–November 2012 is presented.•A new node selection criterion to disconnect airports presented, based on Bonacich power centrality.•This new criterion is compared to a wide range of node selection criteria present in the literature. This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.</description><subject>Air transport</subject><subject>Air transport network</subject><subject>Air transportation industry</subject><subject>Airport closure</subject><subject>Airports</subject><subject>ATN</subject><subject>Complex networks</subject><subject>Computer networks</subject><subject>Computer simulation</subject><subject>Connectivity</subject><subject>Contingency planning</subject><subject>Contingency plans</subject><subject>Criteria</subject><subject>Intentional attacks</subject><subject>Networks</subject><subject>Robustness</subject><subject>Shutdowns</subject><subject>Studies</subject><subject>Transportation</subject><issn>1366-5545</issn><issn>1878-5794</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kM1LxDAQxYMouK7-Ad4KHvTSOvlsiydZ_IIFQfQc0nSKrbvNmqSK_71Z15MHT28Ovzfz5hFySqGgQNXlUESPBQMqCpAFULpHZrQqq1yWtdhPM1cql1LIQ3IUwgCQTJLNyPmTa6YQRwwhc10WXzEzvc-iN2PYOB-zEeOn82_H5KAzq4AnvzonL7c3z4v7fPl497C4XuZWMBZzrlqJlbBoEDnItqpVZw0rGWuwbVEZaCyvG161IAGVErRDy6ztkgpJKZ-Ti93ejXfvE4ao132wuFqZEd0UNFXpTsmhYgk9-4MObvJjSqepFEqWsmYiUXRHWe9C8Njpje_Xxn9pCnpbnR50qk5vq9MgNfyEuNp5MH360aPXwfY4Wmx7jzbq1vX_uL8BRv51yA</recordid><startdate>20140801</startdate><enddate>20140801</enddate><creator>Lordan, Oriol</creator><creator>Sallan, Jose M.</creator><creator>Simo, Pep</creator><creator>Gonzalez-Prieto, David</creator><general>Elsevier India Pvt Ltd</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20140801</creationdate><title>Robustness of the air transport network</title><author>Lordan, Oriol ; Sallan, Jose M. ; Simo, Pep ; Gonzalez-Prieto, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-36d5e84ceaee305d896fca2722bedde6a0bc39b38d050e6641fec2ccf1fe45113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Air transport</topic><topic>Air transport network</topic><topic>Air transportation industry</topic><topic>Airport closure</topic><topic>Airports</topic><topic>ATN</topic><topic>Complex networks</topic><topic>Computer networks</topic><topic>Computer simulation</topic><topic>Connectivity</topic><topic>Contingency planning</topic><topic>Contingency plans</topic><topic>Criteria</topic><topic>Intentional attacks</topic><topic>Networks</topic><topic>Robustness</topic><topic>Shutdowns</topic><topic>Studies</topic><topic>Transportation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lordan, Oriol</creatorcontrib><creatorcontrib>Sallan, Jose M.</creatorcontrib><creatorcontrib>Simo, Pep</creatorcontrib><creatorcontrib>Gonzalez-Prieto, David</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Transportation research. Part E, Logistics and transportation review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lordan, Oriol</au><au>Sallan, Jose M.</au><au>Simo, Pep</au><au>Gonzalez-Prieto, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robustness of the air transport network</atitle><jtitle>Transportation research. Part E, Logistics and transportation review</jtitle><date>2014-08-01</date><risdate>2014</risdate><volume>68</volume><spage>155</spage><epage>163</epage><pages>155-163</pages><issn>1366-5545</issn><eissn>1878-5794</eissn><coden>TRERFW</coden><abstract>•This paper defines a methodology to detect critical airports of the air transport network (ATN).•The methodology is based on the effect of airport disconnection on size of giant component.•A list of critical airports for the global ATN of November 2011–November 2012 is presented.•A new node selection criterion to disconnect airports presented, based on Bonacich power centrality.•This new criterion is compared to a wide range of node selection criteria present in the literature. This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.</abstract><cop>Exeter</cop><pub>Elsevier India Pvt Ltd</pub><doi>10.1016/j.tre.2014.05.011</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1366-5545
ispartof Transportation research. Part E, Logistics and transportation review, 2014-08, Vol.68, p.155-163
issn 1366-5545
1878-5794
language eng
recordid cdi_proquest_miscellaneous_1642273082
source Elsevier ScienceDirect Journals
subjects Air transport
Air transport network
Air transportation industry
Airport closure
Airports
ATN
Complex networks
Computer networks
Computer simulation
Connectivity
Contingency planning
Contingency plans
Criteria
Intentional attacks
Networks
Robustness
Shutdowns
Studies
Transportation
title Robustness of the air transport network
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T07%3A03%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Robustness%20of%20the%20air%20transport%20network&rft.jtitle=Transportation%20research.%20Part%20E,%20Logistics%20and%20transportation%20review&rft.au=Lordan,%20Oriol&rft.date=2014-08-01&rft.volume=68&rft.spage=155&rft.epage=163&rft.pages=155-163&rft.issn=1366-5545&rft.eissn=1878-5794&rft.coden=TRERFW&rft_id=info:doi/10.1016/j.tre.2014.05.011&rft_dat=%3Cproquest_cross%3E1642273082%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1546575924&rft_id=info:pmid/&rft_els_id=S1366554514000805&rfr_iscdi=true