4.7 Article

An attribute fuzzy concept-oriented three-way utility decision model in multi-attribute environments

Journal

APPLIED SOFT COMPUTING
Volume 143, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.asoc.2023.110353

Keywords

Three-way decision; Multi-attribute decision-making; Attribute fuzzy concept; Relative utility function; Generalized conditional probability

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In recent years, an increasing number of researchers have focused on how to leverage limited information to make more reasonable decisions, thereby reducing the decision-making risk for decision-makers. Three-way decision, as a method for risky decision-making, offers a new approach to address this challenge and has gained significant attention. This paper proposes a novel three-way utility decision model oriented to attribute fuzzy concept in multi-attribute environments, based on the utility theory.
In recent years, an increasing number of researchers have focused on how to leverage limited information to make more reasonable decisions, thereby reducing the decision-making risk for decision-makers. Three-way decision, as a method for risky decision-making, offers a new approach to address this challenge and has gained significant attention. In view of this, based on the utility theory, this paper proposes a novel three-way utility decision model oriented to attribute fuzzy concept in multi-attribute environments. Firstly, an attribute fuzzy concept is constructed based on the decisionmaker's minimum requirements on each attribute. Subsequently, a new method for calculating the relative utility function is proposed, which is used to calculate the corresponding decision thresholds. Additionally, a generalized conditional probability calculation method is presented based on the attribute fuzzy concept and the basic semantics of conditional probability. Finally, a new three-way decision model is established to obtain the classification and ranking results of all objects. Through application analysis, comparative study and experimental analysis, the proposed method's rationality and effectiveness are verified.

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