HESITANT FUZZY LINGUISTIC MATRIX GAME AND ITS APPLICATION IN MCDM PROBLEM

Date

2026-01-01

Author

Jana, Jishu
Roy, Sankar Kumar
Weber, Gerhard Wilhelm

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. This study focuses on how to establish a connection between game theory and decision making under an uncertain environment. To tackle this uncertainty, an expansion of the hesitant fuzzy set and linguistic term set, i.e., the hesitant fuzzy linguistic term set (HFLTS), is considered here. The HFLTS is an effective technique for addressing ambiguity or uncertainty in multiple criteria decision making (MCDM). MCDM is a technique of evaluating multiple criteria for the sake of selecting the best alternative. It is an emerging topic in game theory and decision making. Nowadays, researchers are paying more attention to MCDM games with HFLTS. Numerous MCDM techniques are presented in the literature, but very few studies take into account MCDM challenges by using game theoretic models to ascertain the decision makers' preferences and attribute weights. Our main objective is to build the methods for solving an HFLTS-MCDM game. First, we present a novel HFLTS distance measure. To address the hesitant fuzzy linguistic-MCDM game, three novel distance measures, namely HFL-TOPSIS, HFL-VIKOR, and lambda-fuzzy measure, are devised. The resulting outcomes from the three methodologies are compared and contrasted. To exhibit the viability and effectiveness of the suggested measures, we illustrate a real-world example. The numerical results depict that lambda-fuzzy measure is the most suitable approach to find the best alternative among the set of alternatives. Moreover, the Spearman correlation coefficient and p-value between HFL-VIKOR and lambda-fuzzy measure (0.574125and0.045893, respectively) demonstrate the validity and robustness of the results.

URI

https://hdl.handle.net/11511/116540

Collections

Graduate School of Applied Mathematics, Article