Affiliations: [a] School of Business, Sichuan Normal University, Chengdu, P.R. China | [b] School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China | [c] School of Statistics, Southwestern University of Finance and Economics, Chengdu, P.R. China
Correspondence:
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Corresponding author. Fan Lei, School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China. E-mail: [email protected].
Abstract: In recent years, ecological problems have become increasingly serious which are forcing people to give up the past high investment, high consumption and high emission development to promote green growth, implement the green new deal and pay attention to green supply chain research and practice. Therefore, in order to attach great importance to the economic and environmental benefits, enterprises should implement green supply chain and “green” change which has become the trend and urgent. Thus, in order to obtain an optimal green supplier, integration of combined weights and multi-attributive border approximation area comparison (MABAC) under probabilistic uncertain linguistic sets (PULTSs) has offered a novel integrated model, in which information entropy is utilized for calculating objective weights with PULTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems.
Keywords: Multiple attribute group decision making (MAGDM), probabilistic uncertain
linguistic term sets (PULTSs), MABAC method, entropy method, combined weights, green supplier
selection
