Multiple-Attribute Decision Making Based on the Probabilistic Dominance Relationship with Fuzzy Algebras

In multiple-attribute decision-making (MADM) problems, ranking the alternatives is an important step for making the best decision. Intuitionistic fuzzy numbers (IFNs) are a powerful tool for expressing uncertainty and vagueness in MADM problems. However, existing ranking methods for IFNs do not consider the probabilistic dominance relationship between alternatives, which can lead to inconsistent and inaccurate rankings. In this paper, we propose a new ranking method for IFNs based on the probabilistic dominance relationship and fuzzy algebras. The proposed method is able to handle incomplete and uncertain information and can generate consistent and accurate rankings.

Automated summary

In multiple-attribute decision-making problems, ranking the alternatives is crucial for making optimal decisions. Intuitionistic fuzzy numbers are an effective tool for dealing with uncertainty and vagueness in these problems. However, current ranking methods for intuitionistic fuzzy numbers fail to consider the probabilistic dominance relationship, resulting in inconsistent and inaccurate rankings. This paper proposes a new ranking method based on the probabilistic dominance relationship and fuzzy algebras, which can handle incomplete and uncertain information and produce consistent and accurate rankings.