Enhanced MAIRCA technique for green supply chain management based on spherical linear diophantine fuzzy information.

This article focuses on the development and application of spherical q-linear Diophantine fuzzy sets (Sq-LDFSs) integrated with the Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) technique to improve multi-criteria group decision-making (MCGDM) under uncertainty, specifically for green supplier selection (GSS) in supply chain management. Sq-LDFSs extend existing fuzzy set theories by incorporating three membership grades and qth-power control parameters, allowing greater flexibility in handling ambiguous and vague data. The study proposes new weighted aggregation operators based on Sq-LDFSs and demonstrates their effectiveness through a case study involving a chemical processing industry, where multiple experts evaluate suppliers against economic and environmental criteria. Comparative analysis shows that the Sq-LDF-MAIRCA approach provides reliable, adaptable, and realistic decision support, outperforming or aligning closely with existing fuzzy-based methods such as TOPSIS and VIKOR. The methodology is presented as a versatile tool applicable to various complex decision-making problems involving uncertainty and imprecision.