Affiliations: [a] School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China
| [b] School of Business, Sichuan Normal University, Chengdu, P.R. China
Correspondence:
[*]
Corresponding author. Qiang Cai, School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China. E-mail: [email protected]
Abstract: This paper intends to treat the green supplier selection (GSS) problem as a multi-attribute group decision making (MAGDM) problem, adopt the linguistic Z-number that can more flexibly and accurately express the evaluation information, and expand the traditional multi-attribute boundary approximate area comparison (MABAC) method, combine the CRITIC method of standard importance and consider the risk vector to finally determine the optimal solution. More specifically, the linguistic Z-number is used to describe the fuzzy evaluation information of experts on alternatives under attributes, then the expanded CRITIC method is used to obtain the weight of each given attribute, and finally the MABAC method with added risk vector and expanded is used to obtain the ranking of alternatives and obtain the best solution. Finally, taking green supplier selection as an example, and comparing with other methods, the reliability and effectiveness of the constructed method are verified. The results show that this method can express the evaluation information of experts flexibly and completely, and obtain the ranking results of given schemes through fewer steps, which is reliable and effective.
Keywords: Multi-attribute group decision-making (MAGDM), linguistic Z-number (LZN), CRITIC method, MABAC method, green supplier selection, risk vector
