A new approach for fuzzy classification by a multiple-attribute decision-making model

Ranjbar, Mahdi; Effati, Sohrab

doi:10.1007/s00500-022-06912-4

Cited by 8 publications

(1 citation statement)

References 64 publications

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“…The idea of FS was presented by L.A Zadeh [31] to manage the imprecise data, FSs have proved fruitful for decision making. Many researchers produced its application in MADM [32,33,34,35]. After that, the concept of RS theory was proposed by Pawlak [36] and FS and RS were applied to different fields [37,38,39,40].…”

Section: Introductionmentioning

confidence: 99%

Multiple Attribute Decision-Making Based on Bonferroni Mean Operators under Square Root Fuzzy Set Environment

Radenović

Ali

Shaheen

et al. 2022

JCCE

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The intuitionistic fuzzy set, which has a membership and non-membership degree, is a controlling and effective device for dealing with fuzziness and uncertainty. Recently, the square root fuzzy set (SR-FS) which is one of the efficient generalizations of an intuitionistic fuzzy set (IFS) for dealing with uncertainty and haziness in information has been introduced. In this study, a novel method for multiple attribute decision-making (MADM) based on SR-Fuzzy information is investigated. Since aggregation operators are significant in the decision-making process. To achieve this goal, the current paper suggests a variety of novel Bonferroni Mean and Weighted Bonferroni Mean operators to aggregate the SR-Fuzzy values for the various decision-maker preferences. SR-Fuzzy Bonferroni Mean (SRFBM) operator and weighted SR-Fuzzy Bonferroni Mean (WSRFBM) operator are established and describes their properties. Then, we construct a MADM approach using the proposed operators for the SR-Fuzzy information and proved the approach with a mathematical example. In the end, a comparative study of the developed and existing approaches has been discussed to evaluate the pertinency and practicality of the proposed DM technique.

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