Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/346
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dc.contributor.authorKüçükaydın, Hande-
dc.contributor.authorAras, Necati-
dc.date.accessioned2019-02-18T12:27:25Z
dc.date.available2019-02-18T12:27:25Z
dc.date.issued2018-
dc.identifier.citationKucukaydin, H., & Aras, N. (2018) Determining the most vulnerable components in a transportatıon network. Sigma Journal of Engineering and Natural Sciences, 9(4) pp. 371.382.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11779/346-
dc.identifier.urihttp://eds.yildiz.edu.tr/AjaxTool/GetArticleByPublishedArticleId?PublishedArticleId=2755-
dc.description.abstractTransportation networks belong to the class of critical infrastructure networks since a small deterioration in the service provision has the potential to cause considerable negative consequences on everyday activities. Among the reasons for the deterioration we can mention the shutdown of a subway station, the closure of one or more lanes on a bridge, the operation of an airport at a much reduced capacity. In order to measure the vulnerability of transportation network, it is necessary to determine the maximum possible disruption by assuming that there is an intelligent attacker wishing to give damage to the components of the network including the stations/stops and linkages. Identifying the worst disruptions can be realized by using interdiction models that are formulated by a bilevel mathematical programming model involving two decision makers: leader and follower. In this paper, we develop such a model referred to as attacker-operator model, where the leader is a virtual attacker who wants to cause the maximum possible disruption in the transportation network by minimizing the amount of flow among the nodes of the network, while the follower is the system operator who tries to reorganize the flow in the most effective way by maximizing the flow after the disruption. The benefit of such a model to the system operator is to determine the most vulnerable stations and linkages in the transportation network on one hand, and to take precautions in preventing the negative effects of the disruption on the other hand.en_US
dc.description.sponsorshipTUBİTAK Sponsorlu Yayınen_US
dc.language.isoenen_US
dc.publisherYıldız Technical Universityen_US
dc.relation.ispartofSigma Journal of Engineering and Natural Sciencesen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectTransportation networken_US
dc.subjectInterdictionen_US
dc.subjectBilevel programmingen_US
dc.titleDetermining the most vulnerable components in a transportatıon networken_US
dc.typeArticleen_US
dc.authoridHande Küçükaydın / 0000-0003-2527-2064-
dc.description.woscitationindexEmerging Sources Citation Index-
dc.description.WoSDocumentTypeArticle
dc.description.WoSPublishedMonthOcaken_US
dc.description.WoSIndexDate2018en_US
dc.description.WoSYOKperiodYÖK - 2017-18en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.relation.tubitakProje No : ...
dc.identifier.endpage382en_US
dc.identifier.startpage371en_US
dc.identifier.issue4en_US
dc.identifier.volume9en_US
dc.departmentMühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000458617100002en_US
dc.institutionauthorKüçükaydın, Hande-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypeArticle-
crisitem.author.dept02.01. Department of Industrial Engineering-
Appears in Collections:Endüstri Mühendisliği Bölümü koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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