BTWM-HF: A behavioral three-way multi-attribute decision-making method with hesitant fuzzy information

Abstract

Three-way decision (TWD) theory offers a novel paradigm for solving hesitant fuzzy multi-attribute decision-making problems. However, many existing TWD approaches follow the principle of minimum risk, thereby overlooking the influence of the psychological factors of decision-makers (DMs) on decision outcomes when faced with losses and gains. To address this challenge, we propose a behavioral three-way multi-attribute decision-making method with hesitant fuzzy information via hesitant fuzzy TODIM. The proposed method encompasses two key features. One is that the relative utility functions based on the dominance degree are constructed, aiming to portray the psychological behaviors of DMs. The other is the development of an objective calculation of weighted conditional probabilities, achieved without relying on a state set and a binary relation. The feasibility of the proposed method is verified by two numerical examples, one on software selection and the other from the UCI database. The results of the multi-aspect comparative analysis demonstrate that the proposed method exhibits good performance in terms of ranking and classification. Moreover, the experimental results indicate the effectiveness and applicability of the presented method.