R-Set COPRAS (R-COPRAS) Methods-Based Multi-Attribute Decision-Making With RBM and RGBM Operators: A Case Study of Smart Mine Project Safety Assessment

The R-set is modeled by considering the risks associated with sources of information and future events. In the current work, there is no research on the aggregation operator of the R-set, and no in-depth research on its multi-attribute decision-making (MADM) methods. In order to extend the application of R-set more widely, this paper aims to propose a new risk-based fuzzy complex proportional assessment (R-COPRAS) method. First, the R-set Bonferroni mean (RBM) operator and the R-set geometric Bonferroni mean (RGBM) operator are investigated. Then, the correlation properties of these operators are studied. Based on these two operators, COPRAS methods in R-set environment are proposed, which consider the decision risk and can provide stable decision results. Ultimately, a smart mine safety assessment project is proposed to test and check the accuracy and effectiveness of the proposed R-COPRAS methods.