摘要
研究了模糊决策环境下群体评价意见的合成问题。应用距离函数来计算两个梯形模糊数之间的相似性函数,使得相似性函数的应用范围得到拓展。基于熵来度量个体与群体的一致性,建立了群体决策的熵模型,减少了群体的不确定性。利用此模型对专家的初始主观权重进行迭代运算得到修正权重,再把初始主观权重和修正权重线性合成作为专家的综合权重。最后,通过算例说明了该方法的可行性和有效性。
The aim of this paper is to deal with the aggregating problem of group evaluation under fuzzy preference.A new similarity measuring function that is situated between two trapezoidal fuzzy numbers is computed by using distance functions,which makes its applied scope expand.The unanimity between individual and group is measured by utilizing entropy,a group entropy model is established and the uncertainty of the group is reduced.With the aid of the model,the expert＇s original weight is modified to a revised weight by an iterative procedure,and then the expert＇s integrative weight is linear synthesized by original weight and revised weight.Finally,an example is applied to demonstrate the practicability and validity of this approach.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2010年第3期548-551,556,共5页
Systems Engineering and Electronics
基金
浙江省自然科学基金(Y6080215)资助课题
关键词
群决策
一致性
梯形模糊数
熵
group decision making
unanimity
trapezoidal fuzzy number
entropy
