梯形模糊数判断矩阵的二元语义排序方法  

On priority of trapezoidal fuzzy number complementary judgment matrix based on two-tuple linguistic

作　　者：巩在武[1] 

机构地区：[1]南京信息工程大学经济与管理学院,江苏南京210044

出　　处：《系统工程与电子技术》2007年第9期1488-1492,共5页Systems Engineering and Electronics

基　　金：国家自然科学基金(70473037);教育部博士学科点科研基金(20020287001)资助课题

摘　　要：二元语义能够很好地解决信息集结过程中的失真问题,根据二元语义与相应的梯形模糊数等价这一思想,针对群决策过程中梯形模糊数比较的不确定性问题,提出了梯形模糊数互补判断矩阵的一种二元语义的排序方法。讨论了梯形模糊数与二元语义之间的转化方法,建立了二者之间的关系;研究了梯形模糊数互补判断矩阵与二元语义语言判断矩阵之间的内在联系,提出了一种偏好形式为梯形模糊数判断矩阵的极大熵排序方法,给出了梯形模糊数判断矩阵的群集结步骤。算例分析表明所给的排序方法能够有效地避免梯形模糊数评价信息集结过程中信息的丢失与扭曲。Two-tuple linguistic can solve the problem of information being distorted in the process of information aggregating. Based on the principle that two-tuple linguistic and the corresponding trapezoidal fuzzy number are equivalent, and in order to overcome the uncertainty problem of the trapezoidal fuzz numbers comparison, a priority approach to trapezoidal fuzzy number complementary judgment matrix based on the two-tuple linguistic is proposed. The transformation between trapezoidal fuzzy number and two-tuple linguistic is discussed, the relation between them is put forward; using the relationship between trapezoidal fuzzy number complementary judgment matrix and two-tuple linguistic judgment matrix, a maximum entropy priority method is put forward wiht group judgment information taking the form of trapezoidal fuzzy preference, the aggregation steps of collective trapezoidal fuzzy number complementary judgment matrix are given. Finally, it is illustrated by a numerical example that the proposed method can effectiveluy avoid the information being lost and distorted during the process of the trapezoidal fuzzy numbers appraisal information aggregating.

关 键 词：群决策 二元语义 梯形模糊数 互补判断矩阵 极大熵 

分 类 号：C934[经济管理—管理学] O223[理学—运筹学与控制论]