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APPLICATION OF ADAPTIVE NEURO FUZZY INFERENCE SYSTEM TO SUPPLIER SELECTION PROBLEM

dc.contributor.authorYucel, Atakan
dc.contributor.authorGuneri, Ali Fuat
dc.date.accessioned2026-06-27T12:51:47Z
dc.date.issued2010
dc.description.abstractSupplier selection is a key factor for firms in achieving its goals in supply chain management. To build effective relationships and gain competitive advantage, firms should select best supplier(s) according to its needs by applying proper methods and appropriate criteria. Supplier selection problem includes tangible and intangible factors such as quality, cost, relationship closeness and delivery in practice. This issue makes the problem as a Multi-Criteria Decison Making (MCDM) problem. In this paper, an approach that based on neural network and fuzzy logic named as Adaptive Neuro Fuzzy Inference System (ANFIS) is presented for supplier selection problem. The proposed model takes the learning advantage of neural networks and integrates this with fuzzy logic that represents human reasoning mechanism effectively. The basics of ANFIS are illustrated and an algorithm based on the method is proposed for supplier selection problems in the paper.en
dc.identifier.eissn1304-7191
dc.identifier.endpage234
dc.identifier.issn1304-7205
dc.identifier.issue3
dc.identifier.startpage224
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47569
dc.identifier.volume28
dc.identifier.wos000219493000005
dc.language.isotur
dc.publisherYILDIZ TECHNICAL UNIV
dc.relation.ispartofSIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI
dc.subjectSupplier Selection
dc.subjectAdaptive Neuro Fuzzy Inference System
dc.subjectEngineering
dc.titleAPPLICATION OF ADAPTIVE NEURO FUZZY INFERENCE SYSTEM TO SUPPLIER SELECTION PROBLEM
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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