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Approaches to Multiple-Attribute Decision-Making Based on Pythagorean 2-Tuple Linguistic Bonferroni Mean Operators
- Source :
- Algorithms, Vol 11, Iss 1, p 5 (2018), Algorithms; Volume 11; Issue 1; Pages: 5
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- 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.
- Subjects :
- 0209 industrial biotechnology
multiple-attribute decision-making (MADM)
lcsh:T55.4-60.8
Selection (relational algebra)
Computer science
02 engineering and technology
lcsh:QA75.5-76.95
green supply chain management (GSCM)
Theoretical Computer Science
020901 industrial engineering & automation
Operator (computer programming)
0202 electrical engineering, electronic engineering, information engineering
lcsh:Industrial engineering. Management engineering
Pythagorean 2-tuple linguistic numbers (P2TLNs)
Multiple attribute
Numerical Analysis
weighted BM (WBM) operator
Pythagorean theorem
Bonferroni mean
Linguistics
WGBM operator
Computational Mathematics
Computational Theory and Mathematics
green supplier selection
020201 artificial intelligence & image processing
lcsh:Electronic computers. Computer science
Tuple
Subjects
Details
- ISSN :
- 19994893
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Algorithms
- Accession number :
- edsair.doi.dedup.....ec8d75fe6c656cdef83d9b12b59531df