Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4734
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dc.contributor.authorHaldenbilen, Soner-
dc.contributor.authorCeylan, Halim-
dc.date.accessioned2019-08-16T11:36:44Z
dc.date.available2019-08-16T11:36:44Z
dc.date.issued2005-
dc.identifier.issn0308-1060-
dc.identifier.urihttps://hdl.handle.net/11499/4734-
dc.identifier.urihttps://doi.org/10.1080/03081060500515507-
dc.description.abstractThis article proposes new models for estimating transport demand using a genetic algorithm (GA) approach. Based on population, gross national product and number of vehicles, four forms of the genetic algorithm transport planning (GATP) model are developed - one exponential and the others taking quadratic forms - and applied to Turkey. The best fit models in terms of minimum total average relative errors in the test period are selected for future estimation. Demand management strategies are proposed based on three scenarios: restricting private car use, restricting truck use and the simultaneous management of private car use and goods movement. Results show that the GATP model may be used to estimate transport demand in terms of passenger-kilometers traveled (pass-km), vehicle-kilometers traveled (veh-km) and ton-kilometers completed (ton-km). Results also show that the third scenario - simultaneous restrictions on private car use and goods movement - could reduce total veh-km by about 35% by 2025 in this study of Turkish rural roads. © 2005 Taylor & Francis.en_US
dc.language.isoenen_US
dc.relation.ispartofTransportation Planning and Technologyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDemand estimationen_US
dc.subjectDemand managementen_US
dc.subjectGenetic algorithmen_US
dc.subjectTransport planningen_US
dc.subjectTurkeyen_US
dc.subjectGenetic algorithmsen_US
dc.subjectHighway administrationen_US
dc.subjectHighway planningen_US
dc.subjectMathematical modelsen_US
dc.subjectVehiclesen_US
dc.subjectTransport demand managementen_US
dc.subjectMotor transportationen_US
dc.subjectdemand analysisen_US
dc.subjectestimation methoden_US
dc.subjectgenetic algorithmen_US
dc.subjecttransportation planningen_US
dc.subjectEurasiaen_US
dc.titleTransport demand management in Turkey: A genetic algorithm approachen_US
dc.typeArticleen_US
dc.identifier.volume28en_US
dc.identifier.issue6en_US
dc.identifier.startpage403
dc.identifier.startpage403en_US
dc.identifier.endpage426en_US
dc.authorid0000-0002-6548-6481-
dc.authorid0000-0002-4616-5439-
dc.identifier.doi10.1080/03081060500515507-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-33645122189en_US
dc.identifier.wosWOS:000236551600001en_US
dc.identifier.scopusqualityQ2-
dc.ownerPamukkale_University-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
crisitem.author.dept10.02. Civil Engineering-
crisitem.author.dept10.02. Civil Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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