Models for Green Supplier Selection in Green Supply Chain Management With Pythagorean 2-Tuple Linguistic Information

Abstract

In recent years, the environmental problems in China have become more and more serious, for example, resource depletion, environmental pollution, ecological imbalance, and so on. At the same time, the laws and regulations about the environmental protection in the world are constantly introduced, the academic research about the environmental issues is also increasing, more and more consumers show concern for the green products, and the restrictions of the “green trade barrier” in the international to the export products in China enterprises must pay attention to the influence of their behavior on the environment in pursuit of economic efficiency. In this context, the green supply chain management (GSCM) emerges. GSCM theory first appeared in some foreign countries, and started later in China. Compared with some developed countries, the GSCM theory in China is still not mature. From the source speaking, there is lack of a complete GSCM system. In this paper, we combine the generalized weighted Bonferroni mean (GWBM) operator, generalized weighted geometric Bonferroni mean (GWGBM) operator, dual GWBM operator, and dual GWGBM operator with Pythagorean 2-tuple linguistic numbers to propose the generalized Pythagorean 2-tuple linguistic WBM (GP2TLWBM) operator, generalized Pythagorean 2-tuple linguistic WGBM (GP2TLWGBM) operator, dual GP2TLWBM (DGP2TLWBM) operator, and dual GP2TLWGBM (DGP2TLWGBM) operator, and then, the multiple attribute decision-making (MADM) methods are developed based on DGP2TLWBM and DGP2TLWGBM operators. Finally, we use an example for green supplier selection to prove the MADM process of the proposed algorithms.