A theoretical framework of inverse fuzzy soft expert set with application in decision-making

Abstract

Soft sets and their extensions emerge as a powerful tool for handling uncertainty in decision making applications dealing with only one expert. Decision-making involving opinions of more than one expert can be effectively modeled by soft expert sets (SES) and fuzzy soft expert set (FSES). Building upon these concepts this article presents the concept and operations of Inverse Fuzzy Soft Expert Set (inverse FSES) by developing an enhanced algorithmic approach. The Inverse FSES combines the principles of inverse fuzzy sets and SES to model complex decision-making scenarios involving multiple experts. Inverse FSES provides a mechanism to quantify, aggregate and interpret expert judgement with precision. The proposed algorithm is validated using sustainable supplier case study. Sensitivity analysis by changing weights of parameters and by adding credibility weights to experts is also conducted. This article combines the mathematical concept with practical applicability thereby opening a new avenue in decision-making. JEL Codes: D81. Received: 20/04/2025. Accepted: 03/02/2026. Published: 06/08/2026.