2021
DOI: 10.1002/int.22767
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SVNMPR: A new single‐valued neutrosophic multiplicative preference relation and their application to decision‐making process

Abstract: The aim of the paper is to present the concept of a multiplicative preference relation (MPR) with the features of the single‐valued neutrosophic (SVN) set and named as SVN multiplicative preference relation (SVNMPR). The SVN set (SVNS) handles uncertainties more broadly than the intuitionistic fuzzy set by considering the three independent degree systems with a scale rating of 0–1 and is symmetrical about 0.5. However, for asymmetrical distribution, Saaty discusses the 1–9 scale to display the information. Dri… Show more

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Cited by 26 publications
(14 citation statements)
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“…To tackle the same, neutrosophic sets are introduced by Smarandache (Zhang et al 2020). It is extracted from the existing theory of intuitionistic fuzzy sets, natively having the membership function value in terms of the truth, indeterminacy, and falsity function values (Garg 2022). Although the fuzzy set theory answers the uncertainties in the decision-making process, it couldn't effectively handle the indeterminate and inconsistent information (Garg et al 2016).…”
Section: Neutrosophic Based Robust Ranking Approach (Nrra)mentioning
confidence: 99%
“…To tackle the same, neutrosophic sets are introduced by Smarandache (Zhang et al 2020). It is extracted from the existing theory of intuitionistic fuzzy sets, natively having the membership function value in terms of the truth, indeterminacy, and falsity function values (Garg 2022). Although the fuzzy set theory answers the uncertainties in the decision-making process, it couldn't effectively handle the indeterminate and inconsistent information (Garg et al 2016).…”
Section: Neutrosophic Based Robust Ranking Approach (Nrra)mentioning
confidence: 99%
“…, 2019; Pratihar et al. , 2020; Edalatpanah, 2020b, c; Kumar Das, 2020; Garg, 2022; Martin et al. , 2021; Kamacı et al.…”
Section: Introductionmentioning
confidence: 99%
“…So far, numerous studies have been conducted to apply SVN sets for solving decisionmaking problems (Garg, 2020a(Garg, , 2020b(Garg, , 2020c(Garg, , 2022, and as a result, they have been used to solve various problems in a number of decision-making areas such as the economy (Meng et al, 2020), medicine (Zhang et al, 2018;Abdel-Basset et al, 2020), air quality evaluation (Li et al, 2016;Bera and Mahapatra, 2021), and so on. Appropriate extensions that allow the use of SVN sets have also been proposed for a number of MCDM methods, such as TOPSIS (Biswas et al, 2016), PROMETHEE (Xu et al, 2020), AHP (Kahraman et al, 2020), WASPAS (Zavadskas et al, 2015), MULTIMOORA (Stanujkic et al, 2017c), CoCoSo (Rani et al, 2021), and so on.…”
Section: Introductionmentioning
confidence: 99%