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Multiple attribute decision making based on interval-valued Pythagorean uncertain linguistic aggregation operators.

Authors :
Gao, Hui
Wei, Gui-Wu
Source :
International Journal of Knowledge Based Intelligent Engineering Systems. 2018, Vol. 22 Issue 1, p59-81. 23p.
Publication Year :
2018

Abstract

In this paper, we investigate the multiple attribute decision making problems with interval-valued Pythagorean uncertain linguistic information. Then, we utilize arithmetic and geometric operations to develop some interval-valued Pythagorean uncertain linguistic aggregation operators: interval-valued Pythagorean uncertain linguistic weighted average (IVPULWA) operator, interval-valued Pythagorean uncertain linguistic weighted geometric (IVPULWG) operator, interval-valued Pythagorean uncertain linguistic ordered weighted average (IVPULOWA) operator, interval-valued Pythagorean uncertain linguistic ordered weighted geometric (IVPULOWG) operator, interval-valued Pythagorean uncertain linguistic hybrid average (IVPULHA) operator and interval-valued Pythagorean uncertain linguistic hybrid geometric (IVPULHG) operator, some interval-valued Pythagorean uncertain linguistic correlate aggregation operators, some interval-valued Pythagorean uncertain linguistic induced aggregation operators, some interval-valued Pythagorean uncertain linguistic induced correlate aggregation operators and some interval-valued Pythagorean uncertain linguistic power aggregating operators. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the interval-valued Pythagorean uncertain linguistic multiple attribute decision making problems. Finally, a practical example for enterprise resource planning (ERP) system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13272314
Volume :
22
Issue :
1
Database :
Academic Search Index
Journal :
International Journal of Knowledge Based Intelligent Engineering Systems
Publication Type :
Academic Journal
Accession number :
128978215
Full Text :
https://doi.org/10.3233/KES-180375