A method based on preference degrees for handling hybrid multiple attribute decision making problems
A method based on preference degrees for handling hybrid multiple attribute decision making problems
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DOI：
10.1016/j.eswa.2010.08.107
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发表时间：
2011-04
期刊：
影响因子：
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通讯作者：
Xiaohan Yu;Zeshui Xu;Qi Chen
中科院分区：
文献类型：
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作者：
Xiaohan Yu;Zeshui Xu;Qi Chen
本文研究了具有不同形式属性值（真实的数、语言标号、区间数、直觉模糊数和区间直觉模糊数）的混合多属性决策问题。提出了一种基于偏好度的方法，偏好度可以是模糊数、直觉模糊数和区间直觉模糊数。该方法首先将各种形式的属性值归一化为偏好度，然后使用基于偏好度的加权平均算子对归一化的偏好度进行聚合。同时，为了便于计算，提出了一种新的语言表示模型，并与传统的四元组语言表示模型进行了比较，验证了该模型的可行性，同时，该模型还可以构造区间直觉模糊数与语言标号之间的映射关系.最后通过一个应用实例说明了该方法的合理性和实用性。
In this paper, we investigate hybrid multiple attribute decision making problems with various forms of attribute values (real numbers, linguistic labels, interval numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers). We propose a method based on preference degrees which may take the forms of fuzzy numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers. The method first normalizes various forms of attribute values into preference degrees, and then uses a preference degree-based weighted averaging operator to aggregate the normalized preference degrees. Meanwhile, for convenience of calculation, a new linguistic representation model is presented, whose feasibility is verified by comparing it with the traditional 4-tuple linguistic representation model, and from our model, the mapping relationship between interval intuitionistic fuzzy numbers and linguistic labels can be constructed. Finally, we illustrate the rationality and practicality of the proposed method by an application example.