基于云模型的不确定性大群体多属性决策方法

针对传统不确定性大群体多属性决策方法中只考虑决策信息的模糊性，没有考虑信息的随机性这一问题，提出了一种基于云模型的多属性决策方法，从而用于解决由多个小群体组成的不确定性大群体决策问题。首先将不确定语言评价值转化为一维正态云；其次采用决策者主观确定和一致性分析相结合的方法确定针对不同决策对象的小群体权重，进而生成综合云；然后提出了一种改进的云相似度算法作为云模型距离的度量，通过比较各方案综合云与最优云的相似度对方案排序。最后通过实例验证了所提方法的可行性和有效性。

Uncertain multi attribute decision making method for large group based on cloud model

Traditional multi attribute decision making method for large group of uncertainty only considers the burring of decision information, and does not consider the randomness of the information. To solve this problem, a multi attribute decision making method based on cloud model is proposed to solve large group decision making by multiple groups. Firstly, the uncertain linguistic values are converted into the one-dimension normal clouds. After that, the subjective and objective weight determination method based on the decision maker’s subjective determination and consistency analysis are used to determine the small group weights for different decision objects. Then, on this basis integrated cloud is generated; Afterward an improved method of cloud similarity is proposed to measure the distance of cloud models. The order of alternatives can be listed by calculating the similarity between the integrated cloud and optimal cloud. Finally, a practical example is put forward to validate the performance of the proposed method.