Due to apparent flexibility of Intuitionistic Fuzzy Set (IFS) concepts in dealing with the imprecision or uncertainty, these are proving to be quite useful in many application areas for a more human consistent reasoning under imperfectly defined facts and imprecise knowledge. In this paper, we apply notions of entropy and intuitionistic fuzzy sets to present a new fuzzy decision-making approach called intuitionistic fuzzy entropy measure for selection and ranking the suppliers with respect to the attributes. An entropy-based model is formulated and applied to a real case study aiming to examine the rankings of suppliers. Furthermore, the weights for each alternative, with respect to the criteria, are calculated using intuitionistic fuzzy entropy measure. The supplier with the highest weight is selected as the best alternative. This proposed model helps the decision-makers in better understanding of the weight of each criterion without relying on the mere expertise.

由于直觉模糊集 (IFS) 概念在处理不精确或不确定性方面的明显灵活性，事实证明，这些概念在许多应用领域中非常有用，可在不完美定义的事实和不精确知识下进行更加人性化的推理。在本文中，我们应用熵和直觉模糊集的概念来提出一种新的模糊决策方法，称为直觉模糊熵度量，用于根据属性对供应商进行选择和排序。一个基于熵的模型被制定并应用于一个真实的案例研究，旨在检查供应商的排名。此外，关于标准的每个备选方案的权重是使用直觉模糊熵度量计算的。选择权重最高的供应商作为最佳选择。