MABAC method for multiple attribute group decision making under picture 2-tuple linguistic environment
Document Type
Article
Publication Date
4-1-2020
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.
Publication Title
Soft Computing
Volume
24
Issue
8
First Page
5819
Last Page
5829
Digital Object Identifier (DOI)
10.1007/s00500-019-04364-x
ISSN
14327643
E-ISSN
14337479
Citation Information
Zhang, S., Wei, G., Alsaadi, F.E., Hayat, T., Wei, C., Zhang, Z. (2020) MABAC method for multiple attribute group decision making under picture 2-tuple linguistic environment. Soft Computing, 24(8), 5819-5829.