摘要
研究了属性权重信息完全未知、属性值以梯形模糊数形式给出的多属性决策问题,给出了梯形模糊数决策矩阵的规范化公式.把有序加权平均(OWA)算子推广到所给定的数据信息均为梯形模糊数形式的不确定环境中,提出了一种梯形模糊有序加权平均(TFOWA)算子,给出了其在应用过程中的具体步骤,并提出了一种相应的集结决策信息的方法.TFOWA算子的特点是充分利用梯形模糊数的不确定性,因而更能反映客观事物的复杂性及人类思维的模糊性,从而使得决策更符合实际情况.最后通过算例说明了方法的可行性和有效性.
A kind of uncertain multi-attribute decision-making problems is studied, in which the information about the attribute weights is completely unknown and the attribute values are in the forms of trapezoidal fuzzy numbers. Some formulas for normalizing the decision making matrix with trapezoidal fuzzy numbers are given. The ordered weighted averaging （OWA） operator is extended to accommodate uncertain condition where all input arguments take the forms of trapezoidal fuzzy numbers. A trapezoidal fuzzy ordered weighted averaging （TFOWA） operator and its application procedure are proposed, and a method based on the TFOWA operator for aggregating information in decision making is presented. The character of TFOWA operator lies in fully use of uncertainty of trapezoidal fuzzy numbers, so it can reflect the complexity of real world and mistiness of human thought and make the decision making accord with the fact. Finally, a numerical example is given to show the feasibility and effectiveness of the method.
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第6期1034-1038,共5页
Journal of Southeast University：Natural Science Edition
基金
国家自然科学基金资助项目(70472033)
关键词
梯形模糊数
有序加权平均(OWA)算子
多属性决策
trapezoidal fuzzy numbers
ordered weighted averaging（OWA） operator
multi-attribute decision making
作者简介
许叶军（1979-），男，博士生；
达庆利（联系人），男，教授，博士生导师，dql@publicl．ptt．js．cn．
