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A T-spherical fuzzy ELECTRE approach for multiple criteria assessment problem from a comparative perspective of score functions.
- Source :
- Journal of Intelligent & Fuzzy Systems; 2021, Vol. 41 Issue 2, p3751-3770, 20p
- Publication Year :
- 2021
-
Abstract
- The theory involving T-spherical fuzziness provides an exceptionally good tool to efficiently manipulate the impreciseness, equivocation, and vagueness inherent in multiple criteria assessment and decision-making processes. By exploiting the notions of score functions and distance measures for complex T-spherical fuzzy information, this paper aims to propound an innovational T-spherical fuzzy ELECTRE (ELimination Et Choice Translating REality) approach to handling intricate and convoluted evaluation problems. Several newly-created score functions are employed from the comparative perspective to constitute a core procedure concerning concordance and discordance determination in the current T-spherical fuzzy ELECTRE method. By the agency of a realistic application, this paper appraises the usefulness and efficacy of available score functions in the advanced ELECTRE mechanism under T-spherical fuzzy uncertainties. This paper incorporates two forms of Minkowski distance measures into the core procedure; moreover, the effectuality of the advocated measure in differentiating T-spherical fuzzy information is validated. The effectiveness outcomes of the evolved method have been investigated through the medium of an investment decision regarding potential company options for extending the business scope. The real-world application also explores the comparative advantages of distinct score functions in tackling multiple criteria decision-making tasks. Finally, this paper puts forward a conclusion and future research directions. [ABSTRACT FROM AUTHOR]
- Subjects :
- MEMBERSHIP functions (Fuzzy logic)
DECISION making
Subjects
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 41
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 152821081
- Full Text :
- https://doi.org/10.3233/JIFS-211431