Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/3810
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYıldız,Barış-
dc.contributor.authorOlcaytu, Evren-
dc.contributor.authorŞen, Ahmet-
dc.date.accessioned2020-09-18T06:43:05Z-
dc.date.available2020-09-18T06:43:05Z-
dc.date.issued2019-01
dc.identifier.citationYıldız, B., Olcaytu, E., & Şen, A. (2019). The urban recharging infrastructure design problem with stochastic demands and capacitated charging stations. Transportation Research Part B: Methodological, 119, 22-44.en_US
dc.identifier.issn0191-2615
dc.identifier.urihttps://hdl.handle.net/20.500.11851/3810-
dc.identifier.urihttps://doi.org/10.1016/j.trb.2018.11.001-
dc.description.abstractIn this study we develop an exact solution method to optimize the location and capacity of charging stations to satisfy the fast charging needs of electric vehicles in urban areas. Stochastic recharge demands, capacity limitations of charging stations and drivers’ route preferences (deviation tolerances) are simultaneously considered to address this challenging problem faced by recharging infrastructure planners or investors. Taking a scenario based approach to model demand uncertainty, we first propose a compact two stage stochastic programming formulation. We then project out the second stage decision variables from the compact formulation by describing the extreme rays of its polyhedral cone and obtain (1) a cut formulation that enables an efficient branch and cut algorithm to solve large problem instances (2) a novel characterization for feasible solutions to the capacitated covering problems. We test our algorithm on the Chicago metropolitan area network, by considering real world origin-destination trip data to model charging demands. Our results attest the efficiency of the proposed branch and cut algorithm and provide significant managerial insights.en_US
dc.language.isoenen_US
dc.publisherElsevier Ltd.en_US
dc.relation.ispartofTransportation Research Part B: Methodologicalen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCharging station locationen_US
dc.subjectGreen transportationen_US
dc.subjectCapacitated coveringen_US
dc.subjectFlow coveringen_US
dc.subjectInteger programmingen_US
dc.subjectBranch and cuten_US
dc.subjectElectric Vehiclesen_US
dc.titleThe Urban Recharging Infrastructure Design Problem With Stochastic Demands and Capacitated Charging Stationsen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.volume119
dc.identifier.startpage22
dc.identifier.endpage44
dc.relation.tubitakinfo:eu-repo/grantAgreement/TÜBİTAK/MAG/214M211en_US
dc.authorid0000-0002-4179-9627-
dc.identifier.wosWOS:000456900900002en_US
dc.identifier.scopus2-s2.0-85056908432en_US
dc.institutionauthorOlcaytu, Evren-
dc.identifier.doi10.1016/j.trb.2018.11.001-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

14
checked on Dec 21, 2024

WEB OF SCIENCETM
Citations

43
checked on Dec 21, 2024

Page view(s)

128
checked on Dec 23, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.