Decision Making on Multi-valued Rough Neutrosophic Set Using Index Method and Vikor Method

Rough sets provide a robust mathematical framework for handling incomplete and uncertain information. This paper introduces a new approach to enhancing decision-making in university admissions process using Multi-Valued Rough Neutrosophic Sets (MVRNS). We propose two new multi-criteria decision-making (MCDM) methods, based on the Index and VIKOR method for MVRNS. The dataset used in this study is based on expert decision-making, ensuring relevance and accuracy in evaluating the criteria. By addressing uncertainty and vagueness in admission criteria, the proposed methods offer a more efficient and streamlined process compared to existing approaches. A numerical example is provided to demonstrate the practicality and effectiveness of the proposed methods in complex decision-making scenarios.