Three-Way Decisions with Intuitionistic Uncertain Linguistic Decision-Theoretic Rough Sets Based on Generalized Maclaurin Symmetric Mean Operators

Abstract

As a typical model of three-way decisions (3WDs), decision-theoretic rough set (DTRS) has received extensive attention from researchers in the decision-making fields. Intuitionistic uncertain linguistic variables (IULVs) combine the advantages of intuitionistic fuzzy sets (IFSs) and uncertain linguistic variables (ULVs), IULV is more flexible in dealing with uncertain information in decision-making process, and provides a novel means for obtaining loss function (LF) of DTRSs. To get more comprehensive results, a new 3WD model is proposed to solve the multi-attribute group decision-making (MAGDM) problem. First, we gave the LF of DTRSs with IULVs, combined the IULVs and the generalized Maclaurin symmetric mean (GMSM), and proposed the IULGMSM and WIULGMSM operators to aggregate decision information; further, we proposed an intuitionistic uncertain linguistic DTRS model. Then, a method for deducing a new DTRS model is constructed, which can give the corresponding semantic interpretation of the decision results of each alternative. Finally, an example is applied to elaborate the proposed method in detail, and the effects of different conditional probabilities on decision results are discussed.