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Öğe Intuitive fuzzy multi-expert & multi-criteria decision making methodology: An application in healthcare industry(Gazi Universitesi, 2022) Otay, İremAbstract: Fuzzy set extensions have been one of the uncertainty handling tools used in many studies in recent years. Since the 1990s, fuzzy decision making theory has been one of the most studied topics in the literature. Specifically in recent years, many fuzzy decision making models have been proposed by using new fuzzy set extensions. Multi-criteria decision making models have been a research area where these extensions are frequently used. In this study, an integrated AHP-TOPSIS methodology employing triangular intuitionistic fuzzy numbers has been transformed into a methodology in which interval-valued triangular fuzzy numbers can be used. As an application, a surgery robot evaluation and selection problem for a newly founded private hospital to be a part of a hospital chain in Istanbul, has been analyzed. The obtained results showed that different fuzzy set extension based datasets can be successfully used in the same methodology by converting them to each other. In this study, comparison and sensitivity analyses are also performed and it has been observed that the results of the proposed model are quite robust and consistent. © 2022 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.Öğe A novel circular intuitionistic fuzzy AHP&VIKOR methodology: An application to a multi-expert supplier evaluation problem(PAMUKKALE UNIV, 2022-03-16) Otay, İrem; Kahraman, CengizAbstract: VIKOR method being one of the frequently used Multi-Criteria Decision Making (MCDM) methods, is based on the distances of alternatives to positive and negative ideal solutions, and presents compromising solutions. AHP is another MCDM method dividing the big problem into small and manageable problems through pairwise comparisons of criteria and alternatives. In these methods, linguistic assessments are generally preferred since exact numerical assignments of criteria values are really difficult and experts can not reflect the thoughts in their minds with crisp numbers. The fuzzy set theory captures the vagueness and impreciseness in these linguistic assessments successfully thorough fuzzy numbers. Circular intuitionistic fuzzy sets (C-IFS) are the latest extension of ordinary fuzzy sets, which was introduced by Atanassov [1]. C-IFS help experts to define membership (belongingness) and nonmembership (unbelongingness) degrees by incorporating the uncertainty of these degrees. In this paper, an integrated C-IF AHP & CIF VIKOR methodology is developed and applied to a multi-expert supplier evaluation problem. The results obtained from the proposed methodology are compared with other methods, and a sensitivity analysis is performed as well.