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Some Algorithms for Group Decision Making with Intuitionistic Fuzzy Preference Information

机译:具有直觉模糊偏好信息的群体决策算法

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Intuitionistic fuzzy preference relation has turned out to be a powerful structure in representing the decision makers' preference information especially when the decision makers are not able to express their preferences accurately due to the unquantifiable information, incomplete information, unobtainable information, partial ignorance, and so forth. The aim of this paper is to develop some techniques for group decision making with intuitionistic fuzzy preference information. Based on the multiplicative consistency of intuitionistic fuzzy preference relation, three algorithms are proposed for intuitionistic fuzzy group decision making. In the case that the decision makers act as separate individuals, the priority vector of each decision maker can be derived directly from the individual intuitionistic fuzzy preference relation, after which an overall priority vector is obtained by synthesizing those individual priorities together. As for the scenario that the decision makers act as one individual, two different algorithms based on the multiplicative consistency are proposed to deal with this case. The main idea of the former procedure is firstly constructing a social intuitionistic fuzzy preference relation, while that of the later is building a fractional programming model. Some practical examples are given to demonstrate the developed algorithms.
机译:直觉模糊偏好关系已成为代表决策者偏好信息的强大结构,尤其是当决策者由于无法量化的信息,不完整的信息,无法获得的信息,部分的无知等无法准确表达其偏好时。向前。本文的目的是开发一些使用直觉模糊偏好信息进行群体决策的技术。基于直觉模糊偏好关系的乘性一致性,提出了三种用于直觉模糊群决策的算法。在决策者充当单独的个体的情况下,每个决策者的优先级向量可以直接从个体直觉的模糊偏好关系中得出,然后通过将这些个体优先级综合在一起来获得总体优先级向量。对于决策者作为一个个体的情况,提出了两种基于乘法一致性的不同算法来处理这种情况。前一种方法的主要思想是首先构建社会直觉的模糊偏好关系,而后一种方法的主要思想是构建分数规划模型。给出了一些实际的例子来说明所开发的算法。

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