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

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