Sustainable Circular Supplier Selection in the Power Battery Industry Using a Linguistic T-Spherical Fuzzy MAGDM Model Based on the Improved ARAS Method

In the power battery industry, selection of an appropriate sustainable recycling supplier (SCS) is a significant topic in circular supply chain management. Evaluating and selecting SCS for spent batteries considered complex multi-attribute group decision-making (MAGDM) problem closely related to environment, economy, society. The linguistic T-spherical fuzzy (Lt-SF) set (Lt-SFS) combination term (T-SFS), which can accurately describe vague cognition human uncertain environments. Therefore, this article proposes methodology based on improved additive ratio assessment (ARAS) Lt-SFS context. This paper extends Lt-SF generalized distance measure defines similarity measure. Heronian mean (Lt-SFHM) operator its weighted form (i.e., Lt-SFWHM) were developed. Subsequently, new MAGDM model was constructed by integrating LT-SFWHM operator, measure, ARAS method. it, expert weight attribute determined using obtain objective then combined weight. Finally, real case industry presented demonstration. effectiveness practicability method verified through sensitivity analysis comparative study with existing methods.