1. EDAS method for probabilistic linguistic multiple attribute group decision making and their application to green supplier selection
- Author
-
Cun Wei, Yanfeng Guo, and Guiwu Wei
- Subjects
0209 industrial biotechnology ,Computer science ,Circular economy ,Probabilistic logic ,Sorting ,Computational intelligence ,02 engineering and technology ,Fuzzy logic ,Linguistics ,Theoretical Computer Science ,Group decision-making ,Term (time) ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,EDAS ,020201 artificial intelligence & image processing ,Geometry and Topology ,Software - Abstract
In today’s world, environmental problems are becoming increasingly serious, and countries and regions are attaching great importance to them. Low-carbon and circular economy have become a strategic choice for China’s sustainable economic development. As the public’s awareness of environmental protection becomes stronger and stronger, the managers of companies ought to consider the maximum economic benefits. Meanwhile, they are supposed to focus on the green image of enterprises, so as to win in the market competition. The probabilistic linguistic term sets (PLTSs) are useful for expressing uncertain and fuzzy cognitions of the DMs over attributes. In this paper, we extend the Evaluation based on Distance from Average Solution (EDAS) method to the multiple attribute group decision making (MAGDM) with PLTSs. Firstly, concept, comparative formula, and distances of PLTSs are introduced in a nutshell. Then, the extended EDAS method is used to cope with the problems of MAGDM in PLTSs. In addition, for the sake of verifying the applicability of the expanding method, a calculation example about the sorting of green supplier is utilized. Consequently, the example shows that the method is easy to understand and operate. This method can be employed to choose the appropriate solution in other problems of selecting.
- Published
- 2021