Green supplier selection in steel industry with intuitionistic fuzzy Taxonomy method

Author:

Xiao Lu1,Zhang Siqi1,Wei Guiwu1,Wu Jiang2,Wei Cun2,Guo Yanfeng3,Wei Yu4

Affiliation:

1. School of Business, Sichuan Normal University, Chengdu, P.R. China

2. School of Statistics, Southwestern University of Finance and Economics, Chengdu, P.R. China

3. School of Finance, Southwestern University of Finance and Economics, Chengdu, P.R. China

4. School of Finance, Yunnan University of Finance and Economics, Kunming P.R. China

Abstract

Since people around the world have gradually attached importance to resource conservation, various countries are actively taking measures to promote environmental protection and sustainable development. Green supply chain management (GSCM) have emerged in this context. Thus, in this essay, a novel intuitionistic fuzzy multiple attribute group decision making (MAGDM) method is designed to tackle this issue. First of all, CRITIC (Criteria Importance Through Inter-criteria Correlation) method is utilized to determine the weights of criteria. Later, the conventional Taxonomy method is extended to the intuitionistic fuzzy environment to compute the value of development attribute of each supplier. Then, the optimal one can be determined. Eventually, an application about green supplier selection in steel industry is presented, and a comparative analysis is made to demonstrate the superiority of the proposed method. The main features of the proposed algorithm are that they provide a practical solution for selecting GSCM and presents an objective weighting method to enhance the effectiveness of the algorithm.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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3. MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment;Wang;Defence Technology,2020

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