基于证据推理的直觉模糊多属性群决策方法

针对属性值为直觉模糊数的多属性群决策问题,提出了一种证据推理的扩展方法。首先,在考虑主观因素与客观因素的基础上运用直觉模糊熵法计算出属性及专家的综合权重。其次,提出一种基于证据推理的直觉模糊信息融合方法,该方法可以避免由于评价值的隶属度为0而导致的信息丢失现象,弥补了现有直觉模糊信息融合方法存在的不足。在此基础上,集结评价信息并按照备选方案与理想方案的相对贴近度对备选方案进行比选。最后,运用实例验证了所提方法的有效性。

Intuitionistic Fuzzy multi-Attribute Group Decision-making Method Based on Evidential Reasoning

This paper proposes a new decision-making method for the problem of multi-attribute group decision making, in which attribute values are intuitionistic fuzzy numbers. At first, the synthetic weights of attributes and experts are computed by the intuitionistic fuzzy entropy according to the subjective and objective factors. Then, an intuitionistic fuzzy information fusion method based on evidential reasoning is proposed. This method can avoid information loss caused by the membership degree being zero and make up for the shortcomings of the existing fuzzy information fusion methods. Based on this, the evaluation information is aggregated and alternatives are ranked according to the relative closeness coefficients of each alternative to the ideal alternative. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed method.