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Approaches to Multiple-Attribute Decision-Making Based on Pythagorean 2-Tuple Linguistic Bonferroni Mean Operators

by 1, 2 and 1,*
1
School of Business, Sichuan Normal University, Chengdu 610101, China
2
College of Mathematics and Software Science, Sichuan Normal University, Chengdu 610066, China
*
Author to whom correspondence should be addressed.
Algorithms 2018, 11(1), 5; https://doi.org/10.3390/a11010005
Received: 30 November 2017 / Revised: 6 January 2018 / Accepted: 9 January 2018 / Published: 12 January 2018
In this paper, we investigate multiple-attribute decision-making (MADM) with Pythagorean 2-tuple linguistic numbers (P2TLNs). Then, we combine the weighted Bonferroni mean (WBM) operator and weighted geometric Bonferroni mean (WGBM) operator with P2TLNs to propose the Pythagorean 2-tuple linguistic WBM (P2TLWBM) operator and Pythagorean 2-tuple linguistic WGBM (P2TLWGBM) operator; MADM methods are then developed based on these two operators. Finally, a practical example for green supplier selection is given to verify the developed approach and to demonstrate its practicality and effectiveness. View Full-Text
Keywords: multiple-attribute decision-making (MADM); Pythagorean 2-tuple linguistic numbers (P2TLNs); weighted BM (WBM) operator; WGBM operator; green supplier selection; green supply chain management (GSCM) multiple-attribute decision-making (MADM); Pythagorean 2-tuple linguistic numbers (P2TLNs); weighted BM (WBM) operator; WGBM operator; green supplier selection; green supply chain management (GSCM)
MDPI and ACS Style

Tang, X.; Huang, Y.; Wei, G. Approaches to Multiple-Attribute Decision-Making Based on Pythagorean 2-Tuple Linguistic Bonferroni Mean Operators. Algorithms 2018, 11, 5.

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