31-07-2024 | Correspondence
Fermatean Fuzzy Dombi Generalized Maclaurin Symmetric Mean Operators for Prioritizing Bulk Material Handling Technologies
Authors:
Abhijit Saha, Svetlana Dabic-Miletic, Tapan Senapati, Vladimir Simic, Dragan Pamucar, Ali Ala, Leena Arya
Published in:
Cognitive Computation
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Excerpt
The idea of a “fuzzy set (FS)” [
1] was conceived primarily to account for equivocal human judgments when solving real-world situations. Alternately, the FSs doctrine can govern the reality emerging through computationally based perception and understanding, which is characterized by uncertainty, partial affiliation, and incorrectness [
2]. Atanassov [
3] suggested “intuitionistic fuzzy sets (IFSs),” which are shown by the “membership degree (MD)” and “non-membership degree (NMD),” with the limitation that the total of MD and NMD cannot exceed one. As an extension of FS, IFS has evolved as an important technique for explaining the uncertainty and ambiguity of real-world problems due to its distinct advantages [
4]. Yager [
5] has invented the “Pythagorean fuzzy set (PFS)” which is characterized by the MD and NMD and satisfies the restriction of a squaring sum of the MD and NMD is limited to one. Subsequently, PFSs outperform IFSs when it comes to dealing with uncertainties and ambiguous data in real-world scenarios [
6‐
8]. Although in a number of real-world decision-making scenarios, an expert’s opinion may serve as the deciding factor (0.9, 0.5). Because 0.9 + 0.5 > 1 and 0.81 + 0.25 > 1, IFS and PFS appear incapable of addressing these difficulties. To clarify this issue, Senapati and Yager [
9] developed the notion of “Fermatean fuzzy sets (FFSs).” The MD and NMD exhibit the FFSs so that the addition of their cubes cannot exceed one [
10,
11]. Therefore, compared to IFSs and PFSs, FFSs are stronger and more effective in solving ambiguous “multi-criteria decision-making (MCDM)” situations [
12]. …
