The Intuitionistic Fuzzy Electre Model

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Date

2018

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Taylor & Francis Ltd

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

The purpose of this research is to postulate and define a new model for Multi-Criteria DecisionMaking (MCDM) problems utilizing the Intuitionistic Fuzzy ELimination Et Choix Traduisant la REalite (IFELECTRE) method, otherwise identified as the Intuitionistic Fuzzy Index of Hesitation Degree method. The Intuitionistic Fuzzy Sets (IFS) method offers certain advantages in using vagueness over a Fuzzy Set (FS): the IFELECTRE method is used to handle more complicated problems, whereas the Decision-Makers (DMs) have some vagueness in assigning option values to the objects considered. The processes of evaluating qualitative and quantitative scales are combined in this work and the proposed model enables different DMs to assess and use IFS. The original ELECTRE method cannot be operated effectively owing to a lack of precise information under different conditions.

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Erdebilli, Babek/0000-0001-8860-3903
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Keywords

Multi-Criteria Decision-Making (MCDM), Decision-Makers (DMs), ELimination Et Choix Traduisant la REalite (ELECTRE), Intuitionistic Fuzzy Set (IFS)

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Q1

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Volume

13

Issue

2

Start Page

139

End Page

145

URI

https://doi.org/10.1080/17509653.2017.1349625
 https://hdl.handle.net/20.500.14411/3010

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