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Interval-Valued Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making
- Source :
- IEEE Access, Vol 6, Pp 67866-67884 (2018)
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- Interval-valued Pythagorean fuzzy (IVPF) set is one the successful extension of the existing theories for handling the uncertainties during the decision-making process. Under that environment, various aggregation operators have been developed by the authors to aggregate the different preferences of the decision makers under the different attributes. But these studies have conducted under the assumption that their corresponding pairs are independent and don’t consider the interaction between the pairs of the membership degrees. In this paper, these conditions have been relaxed by considering the interrelationship between the different inputs by using Maclaurin symmetric mean (MSM) operator. Further, based on the input and MSM operator, we proposed two aggregation operators namely, IVPF Maclaurin symmetric mean and IVPF weighted Maclaurin symmetric mean operators and studied their desirable properties. A decision-making method based on these operators has been discussed for solving the decision-making problems under IVPF set environment. Finally, an illustrative example and a comparative analysis have been presented to demonstrate the proposed approach.
- Subjects :
- 0209 industrial biotechnology
General Computer Science
Multiple attribute decision making (MADM)
Fuzzy set
02 engineering and technology
aggregation operators
emerging technology commercialization
Fuzzy logic
Set (abstract data type)
020901 industrial engineering & automation
Operator (computer programming)
potential evaluation
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Mathematics
Aggregate (data warehouse)
Pythagorean theorem
General Engineering
Process (computing)
Extension (predicate logic)
MSM operator
Algebra
020201 artificial intelligence & image processing
lcsh:Electrical engineering. Electronics. Nuclear engineering
IVPFS
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....8d68bb8bc36cc73cac2d8d69f6080658