<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-23T17:03:26Z</responseDate><request verb="GetRecord" identifier="oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/12561" metadataPrefix="oai_dc">https://gumushane-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/12561</identifier><datestamp>2026-10-22T11:35:37Z</datestamp><setSpec>openaire</setSpec><setSpec>driver</setSpec><setSpec>com_gumushane_10000</setSpec><setSpec>col_gumushane_10001</setSpec><setSpec>com_gumushane_10007</setSpec><setSpec>col_gumushane_10171</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:title>Extension of TODIM Method Based on Distance Measures of Decomposed Fuzzy Sets</dc:title><dc:creator>Köseoğlu, Ali</dc:creator><dc:creator>Şahin, Rıdvan</dc:creator><dc:contributor>Kahraman, C.</dc:contributor><dc:contributor>Cevik Onar, S.</dc:contributor><dc:contributor>Cebi, S.</dc:contributor><dc:contributor>Oztaysi, B.</dc:contributor><dc:contributor>Ucal Sari, I.</dc:contributor><dc:contributor>Tolga, A.C.</dc:contributor><dc:subject>Decomposed Fuzzy Sets</dc:subject><dc:subject>Distance Measures</dc:subject><dc:subject>TODIM method</dc:subject><dc:description>Fuzzy sets allow elements to have partial membership in a set, represented by a membership value between 0 and 1. This feature enables fuzzy sets to model imprecise or vague concepts. Decomposed fuzzy sets, an extension of fuzzy sets, have introduced a novel perspective in the literature by incorporating the Kano model into risk assessment. These sets have also paved the way for new approaches in decision-making methods, highlighting their functional and dysfunctional elements. In this paper, we propose a distance measure for decomposed fuzzy sets and subsequently extend the TODIM method based on this distance measure to DFSs. Then, we provide a numerical example to illustrate its effectiveness and practicality.</dc:description><dc:publisher>Springer Science and Business Media Deutschland GmbH</dc:publisher><dc:date>2024</dc:date><dc:type>Conference Object</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/gumushane/12561</dc:identifier><dc:identifier>https://doi.org/10.1007/978-3-031-70018-7_78</dc:identifier><dc:identifier>978-303170017-0</dc:identifier><dc:identifier>2367-3370</dc:identifier><dc:language>en</dc:language><dc:relation>Lecture Notes in Networks and Systems</dc:relation><dc:rights>info:eu-repo/semantics/openAccess</dc:rights><dc:type>info:eu-repo/semantics/conferenceObject</dc:type><dc:identifier>https://gumushane-rdlopen.rawdatalibrary.net/tr/items/gumushane/12561</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>