基于直觉模糊动态信息交互的多属性群决策模型

Model of multi-attribute group decision making based on intuitionistic fuzzy dynamic interactive information

针对目前的多属性群决策研究中很少考虑信息交互环节等问题,提出一种基于直觉模糊动态信息交互的多属性群决策模型。模型中用直觉模糊集表示决策属性值,通过定义两直觉模糊集的相似度,计算各个专家对方案的偏好矢量与理想方案偏好矢量间的相似度。通过计算群体的平均相似度和专家的决策偏差,若决策偏差大于给定阈值,则通过信息交互对决策偏好进行修正,直到所有的专家的决策偏差都小于给定阈值为止。计算各个方案与理想方案的加权相似度,按加权相似度排列,根据加权相似度最大原则选出最优方案。最后,通过结合1个实际案例讨论本模型的实施步骤,并与未考虑动态信息交互的模糊动态信息群决策方法进行比较,结果证明它是可行和有效的。

Considering that the information interaction in the multi-attribute group decision-making model is not taken into consideration, a model for multi-attribute group decision-making was developed based on fuzzy dynamic information. In the model, intuitionistic fuzzy set（IFS） was used to measure the value of attribute, define the similarity between two IFSs and compute the similarity between the individual preference vectors and ideal preference vector on the cases. By calculating the average similarity of groups and the deviation of individual decision-making, the model could refine the decision-making preference until the deviations of individual decision-making were all less than a given threshold. A optimal solution was put forward based on the ranking of the weighted similarity between individual decision-making in ideal decision-making. The model is demonstrated applicable and effective by providing a case study on the application steps in comparison with the model without incorporating dynamic information.