Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/10123
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dc.contributor.authorAyvaz, Mustafa Tamer-
dc.contributor.authorKentel, Elçin-
dc.date.accessioned2019-08-16T13:11:56Z
dc.date.available2019-08-16T13:11:56Z
dc.date.issued2015-
dc.identifier.issn0733-9496-
dc.identifier.urihttps://hdl.handle.net/11499/10123-
dc.identifier.urihttps://doi.org/10.1061/(ASCE)WR.1943-5452.0000473-
dc.description.abstractA fuzzy decision-making framework (DMF) is combined with a hybrid genetic algorithm-linear programming (GA-LP) optimization approach to determine the best booster station network for a water distribution system. The proposed hybrid GA-LP model simultaneously optimizes two conflicting objectives; namely, minimization of total chlorine injection dosage and the number of booster stations. At the same time, residual chlorine concentrations are kept within desired limits. Adjustment of the relative importance of two conflicting objectives results in different optimal solutions. Selection of the best alternative among these optimal solutions is performed through a fuzzy multiobjective DMF. The proposed DMF allows incorporation of the decision makers' preferences into the booster station network design. In this study, three fuzzy objectives are selected based on economic, operational, and health-related concerns. The hybrid GA-LP model is applied to a case study, and results show that the proposed methodology is effective in maintaining chlorine residuals within desired limits networkwide while minimizing the total chlorine injection, and the fuzzy DMF is a useful tool for incorporating the case specific limitations into the decision process. © 2014 American Society of Civil Engineers.en_US
dc.language.isoenen_US
dc.publisherAmerican Society of Civil Engineers (ASCE)en_US
dc.relation.ispartofJournal of Water Resources Planning and Managementen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBooster station networken_US
dc.subjectFuzzy decision makingen_US
dc.subjectHybrid genetic algorithm-linear programming (GA-LP) modelen_US
dc.subjectResidual chlorineen_US
dc.subjectAlgorithmsen_US
dc.subjectChlorineen_US
dc.subjectGenetic algorithmsen_US
dc.subjectLinear programmingen_US
dc.subjectOptimal systemsen_US
dc.subjectWater distribution systemsen_US
dc.subjectWater supply systemsen_US
dc.subjectChlorine residualsen_US
dc.subjectConflicting objectivesen_US
dc.subjectFuzzy Decision makingen_US
dc.subjectHybrid genetic algorithmsen_US
dc.subjectOptimal solutionsen_US
dc.subjectOptimization approachen_US
dc.subjectResidual chlorinesen_US
dc.subjectStation networken_US
dc.subjectDecision makingen_US
dc.subjectchlorineen_US
dc.subjectconcentration (composition)en_US
dc.subjectdecision makingen_US
dc.subjectdistribution systemen_US
dc.subjectfuzzy mathematicsen_US
dc.subjectidentification methoden_US
dc.subjectresidual flowen_US
dc.subjectwater resourceen_US
dc.titleIdentification of the best booster station network for a water distribution systemen_US
dc.typeArticleen_US
dc.identifier.volume141en_US
dc.identifier.issue5en_US
dc.identifier.doi10.1061/(ASCE)WR.1943-5452.0000473-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-84988269469en_US
dc.identifier.wosWOS:000354098900007en_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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