Abstract:

Hierarchical evaluation index system model was established for order important degree, order important degree evaluation method was put forward based on fuzzy hierarchy group entropy. In this method, in view of the first appraisal criterion levels weight, participating score experts weight equally and not the equal question, uses more succinct group eigenvalue method（GEM）and relative entropy model(REM) separately carries on the computation. The information content of target data in the evaluating indicator system was measured to confirm the weight of different plan. The dimension value of stationary index was effective transformed by using fuzzy mathematics. The application example has proven this method validity solving the appraisal problem in the order importance degree evaluation.

Key words:

Entropy,    , AHP,    , Group decision-making,   ,  Fussy math,   , Order importance degreemso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-font-family: 宋体, mso-fareast-theme-font: minor-fareast, mso-hansi-font-family: Calibri, mso-hansi-theme-font: minor-latin">

摘要： 建立了订单重要度递阶层次评价指标体系模型, 提出了基于模糊层次群熵的订单重要度评价方法。在该方法中, 针对第一评价准则层的权重, 参加打分专家的权重相等与不相等的问题, 分别用相对于两两比较更为简洁的群决策特征根法和具有良好集结性的群决策相对熵模型算法来进行计算;用熵来度量评价指标体系中指标数据所蕴含的信息量, 以确定不同方案的权重;用模糊数学对定性指标的量纲数值, 进行有效的转化。应用实例证明了该方法的有效性, 解决了订单重要度评价中定性与定量相结合的评价问题。

关键词: 熵 , AHP , 群决策 , 模糊数学 , 订单重要度