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dc.contributor.authorSimsek, Baris
dc.contributor.authorIc, Yusuf Tansel
dc.contributor.authorSimsek, Emir Huseyin
dc.date.accessioned2019-09-17T08:27:41Z
dc.date.available2019-09-17T08:27:41Z
dc.date.issued2016
dc.identifier.issn1875-6891
dc.identifier.urihttps://www.atlantis-press.com/journals/ijcis/25868709
dc.identifier.urihttp://hdl.handle.net/11727/3912
dc.description.abstractIn this study, a fuzzy multi-response standard ready-mixed concrete (SRMC) optimization problem is addressed. This problem includes two conflicting quality optimization objectives. One of these objectives is to minimize the production cost. The other objective is to assign the optimal parameter set of SRMC's ingredient to each activity. To solve this problem, a hybrid fuzzy multi-response optimization and artificial neural network (ANN) algorithm is developed. The ANN algorithm is integrated into the multi-response SRMC optimization framework to predict and improve the quality of SRMC. The results show that fuzzy multi-response optimization model is more effective than crisp multi-response optimization model according to final production cost. However, the ANN model also gave more accurate results than the fuzzy model considering the regression analysis results.en_US
dc.language.isoengen_US
dc.relation.isversionof10.1080/18756891.2016.1175816en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectStandard ready-mixed concreteen_US
dc.subjectMulti-response optimizationen_US
dc.subjectTaguchi methoden_US
dc.subjectFuzzy TOPSISen_US
dc.subjectArtificial neural networksen_US
dc.titleHybridizing a fuzzy multi-response Taguchi optimization algorithm with artificial neural networks to solve standard ready-mixed concrete optimization problemsen_US
dc.typearticleen_US
dc.relation.journalINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMSen_US
dc.identifier.volume9en_US
dc.identifier.issue3en_US
dc.identifier.startpage525en_US
dc.identifier.endpage543en_US
dc.identifier.wos000373756900009en_US
dc.identifier.scopus2-s2.0-84963706099en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergien_US


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