Akademik Məlumat İdarəetmə Sistemi
Energy Reports, vol.13, pp.5773-5791, 2025 (SCI-Expanded, Scopus)
One of the most significant competitive issues modern businesses face is the supplier selection dilemma. Choosing the best green supplier is a complex, multifaceted problem since businesses need to enhance how they manage a supply chain that respects green methods and innovations to boost sustainability. Finding sets of criteria and accumulating domain knowledge have received comparatively less attention in research, with most studies concentrating on developing and improving novel techniques. A circular intuitionistic fuzzy set (Cr-IFS) is a well-known and efficient aggregation model. The primary feature of this study is to develop some flexible operations of Frank aggregation operators in the light of the circular intuitionistic fuzzy (Cr-IF) context. These Frank operators offer smooth and reliable aggregated results during the aggregation process. A family of robust aggregation models is derived to express the expert's opinion and judgments by the decision maker, including Cr-IF Frank weighted average (Cr-IFFWA) and Cr-IF Frank weighted geometric (Cr-IFFWG) operators. Some desirable characteristics and exceptional cases are also demonstrated to highlight validity and effectiveness. A robust decision algorithm for the multi-attribute group decision-making (MAGDM) problem is established to prove the compatibility of diagnosed research work. To examine the stability of the derived mathematical approaches, an experimental case study is presented within the context of green supplier selection. To explore the advantages of pioneering techniques, a comprehensive comparative analysis is needed to prove the superiority of existing theories.