On Multicriteria Decision-Making Method Based on a Fuzzy Rough Set Model With Fuzzy α-Neighborhoods

In this article, a novel fuzzy alpha-neighborhood operator with reflexivity is constructed and a new fuzzy rough set model based on the fuzzy alpha-neighborhood operator is proposed. Aiming at decision-making in information systems with real-valued information systems (RVISs), we first utilize data normalization method to effectively transform RVISs into information systems with fuzzy-valued information systems (FVISs). Then, we use the fuzzy alpha-neighborhood-based fuzzy rough set model to convert FVISs into information systems with intuitionistic fuzzy-valued information systems (IFVISs). By adopting the idea of the PROMETHEE II method, we develop three different sorting decision-making schemes on IFVISs, which consist of the subtraction of intuitionistic fuzzy numbers, sorting functions, and intimacy coefficients. Finally, numerical experiments demonstrate the effectiveness of our method. Comparative studies and Spearman rank correlation analyses explain the superiority of our schemes. Experimental results verify the stability of the performance of our strategy.

Automated summary

This article introduces a novel fuzzy alpha-neighborhood operator and a fuzzy rough set model based on this operator for decision-making in information systems. By utilizing data normalization and the fuzzy alpha-neighborhood-based fuzzy rough set model, real-valued information systems are effectively transformed into intuitionistic fuzzy-valued information systems, with three different sorting decision-making schemes developed on the latter. The method is validated through numerical experiments and comparative studies, demonstrating its stability and effectiveness.