Journal
SOFT COMPUTING
Volume 24, Issue 8, Pages 5819-5829Publisher
SPRINGER
DOI: 10.1007/s00500-019-04364-x
Keywords
Multiple attribute group decision making (MAGDM); Picture 2-tuple linguistic sets (P2TLSs); MABAC model; P2TLNs MABAC model; Renewable energy power generation project
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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.
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