Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4537
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dc.contributor.authorCeylan, Halim-
dc.date.accessioned2019-08-16T11:34:46Z
dc.date.available2019-08-16T11:34:46Z
dc.date.issued2006-
dc.identifier.issn0733-947X-
dc.identifier.urihttps://hdl.handle.net/11499/4537-
dc.identifier.urihttps://doi.org/10.1061/(ASCE)0733-947X(2006)132:8(663)-
dc.description.abstractThis study develops a genetic algorithm with TRANSYT hill-climbing optimization routine, referred to as GATHIC, and proposes a method for decreasing the search space, referred to as ADESS, to find optimal or near-optimal signal timings for area traffic control (ATC). The ADESS with GATHIC model is an algorithm, which solves the ATC problem to optimize signal timings for all signal controlled junctions by taking into account coordination effects. The flowchart of the proposed model with ADESS algorithm is correspondingly given. The GATHIC is applied to a well-known road network in literature for fixed sets of demand. Results showed that the GATHIC is better in signal timing optimization in terms of optimal values of timings and performance index when it is compared with TRANSYT, but it is computationally demanding due to the inclusion of the hill-climbing method into the model. This deficiency may be removed by introducing the ADESS algorithm. The GATHIC model is also tested for 10% increased and decreased values of demand from a base demand. © 2006 ASCE.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Transportation Engineeringen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlgorithmsen_US
dc.subjectOptimization modelsen_US
dc.subjectTraffic controlen_US
dc.subjectTraffic delayen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMathematical modelsen_US
dc.subjectOptimizationen_US
dc.subjectTraffic signalsen_US
dc.subjectArea traffic controlen_US
dc.subjectSignal timing optimizationen_US
dc.subjectSignal timingsen_US
dc.subjectHighway traffic controlen_US
dc.subjectgenetic algorithmen_US
dc.subjectnumerical modelen_US
dc.subjectoptimizationen_US
dc.subjecttraffic managementen_US
dc.titleDeveloping combined genetic algorithm - Hill-climbing optimization method for area traffic controlen_US
dc.typeArticleen_US
dc.identifier.volume132en_US
dc.identifier.issue8en_US
dc.identifier.startpage663
dc.identifier.startpage663en_US
dc.identifier.endpage671en_US
dc.authorid0000-0002-4616-5439-
dc.identifier.doi10.1061/(ASCE)0733-947X(2006)132:8(663)-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-33746079193en_US
dc.identifier.wosWOS:000239075100008en_US
dc.identifier.scopusqualityQ1-
dc.ownerPamukkale_University-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
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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