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Fabric Selection Problem Based on Sine Hyperbolic Fractional Orthotriple Linear Diophantine Fuzzy Dombi Aggregation Operators

Authors :
Muhammad Qiyas
Muhammad Naeem
Neelam Khan
Faisal Khan
Source :
IEEE Access, Vol 11, Pp 76883-76903 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

The paper aims are to impersonate some robust sine-hyperbolic operations laws to determine the group decision-making process under the fractional orthotriple linear Diophantine fuzzy set (FOLDFS) situation. The FOLDFS has a notable feature to trade with the dubious information with a broader membership representation space than the Spherical fuzzy set. Based on it, the present paper is classified into three phases. The first phase is to introduce new operational laws for FOLDFS using Dombi operational laws. The main idea behind the proposed operations is to incorporate the qualities of the sine hyperbolic function, namely periodicity and symmetric about the origin towards the decisions of the objects. Secondly, based on these laws, numerous operators (sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi weighted averaging, sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi ordered weighted averaging, sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi hybrid averaging, sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi weighted geometric, sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi ordered weighted geometric, sine hyperbolic fractional orthotriple linear Diophantine fuzzy Dombi hybrid geometric) to aggregate the information are acquired along with their requisite properties and relations. Finally, an algorithm to interpret the multi-attribute group decision making problem is outlined based on the stated operators and manifest it with an illustrative example. A detailed comparative interpretation is achieved with some of the existing methods to reveal their influences.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.756bfcc2166a4dcb9320a3596bfcadc0
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2023.3295112