基于云模型的区间直觉模糊数多属性群决策

针对属性值为区间直觉模糊数的多属性群决策问题, 考虑到模糊性和随机性对群决策过程及结果的影响, 本研究将利用云模型理论结合区间直觉模糊数的特征, 运用灰色关联系数法和信息熵理论确定专家和属性权重, 通过信息集结构建综合评价云模型. 不同于传统的区间直觉模糊数的排序方法, 本研究利用云模型的3En规则将区间直觉模糊数进行云转换并通过云相似度确定方案的综合评价值和犹豫度, 然后对决策方案进行比较分析. 研究结果表明: 该方法能够科学有效地进行决策, 进而为决策方提供科学依据.

Multi-attribute Group Decision-making for Interval-valued Intuitionistic Fuzzy Numbers Based on Cloud Model

Focusing on multi-attribute group decision-making with interval-valued intuitionistic fuzzy numbers as the attribute values, this study uses the grey correlation coefficient method and the information entropy theory to determine the weights of experts and attributes and builds a comprehensive evaluation cloud model through information aggregation. For this purpose, the influences of fuzziness and randomness on the process and results of group decision-making are taken into account, and the cloud model theory and the characteristics of interval-valued intuitionistic fuzzy numbers are leveraged. Different from the traditional ranking method for interval-valued intuitionistic fuzzy numbers, this study uses the 3En rule of the cloud model to convert interval-valued intuitionistic fuzzy numbers into the cloud and determines the comprehensive evaluation value and hesitation degree of the scheme through cloud similarity. Then, the decision-making schemes are comparatively analyzed. The results show that the proposed method can make decisions scientifically and effectively and thereby provide a scientific basis for decision-makers.