Paper Info
Title
MABAC method for multiple attribute group decision making under picture 2-tuple linguistic environment
Abstract
In this article, we extend multi-attributive border approximation area comparison (MABAC) approach to the multiple attribute group decision making with picture 2-tuple linguistic numbers. We review the concept of picture 2-tuple linguistic sets and introduce its corresponding score function, accuracy function, and operational laws. In addition, we propose two aggregation operators of picture 2-tuple linguistic numbers and then develop a method by combining traditional MABAC model with the overall picture 2-tuple linguistic evaluation information. Our proposed method is increasingly accurate and valid even when the conflicting attributes are considered. We also provide a numerical instance for assessing and selecting the renewable energy power generation project to demonstrate the efficacy of our novel model. Finally, we compare our proposed approach with other traditional operators to further show its benefits.
Year
DOI
Venue
2020
10.1007/s00500-019-04364-x
Soft Computing
Keywords
DocType
Volume
Multiple attribute group decision making (MAGDM), Picture 2-tuple linguistic sets (P2TLSs), MABAC model, P2TLNs MABAC model, Renewable energy power generation project
Journal
24
Issue
ISSN
Citations 
8
1432-7643
3
PageRank 
References 
Authors
0.40
0
6
Name
Order
Citations
PageRank
Siqi Zhang141.08
Gui-Wu Wei216319.00
Fuad E. Alsaadi31818102.89
Tasawar Hayat499971.98
Cun Wei5195.66
Zuopeng Zhang651.76