一种基于梯形模糊语言变量的多属性决策方法

针对属性权重未知、属性值以梯形模糊语言变量形式给出的多属性决策问题,提出了一种扩展的VIKOR决策方法。首先介绍了梯形模糊语言变量的概念、运算法则,提出了梯形模糊语言变量值之间的距离公式,并进行了证明。在此基础上利用离差最大化方法确定了属性指标权重,并建立了基于梯形模糊语言变量的扩展VIKOR方法,给出了决策步骤。最后,通过一个算例说明该方法的有效性。

Pythagorean梯形模糊语言集结算子及其应用

为了解决Pythagorean模糊语言集不能处理梯形模糊信息环境下的多属性群决策问题,本文基于Pythagorean模糊语言集的定义,提出了一类新的模糊集——-Pythagorean梯形模糊语言集,并给出了相应的运算规则、得分函数和大小比较原则;之后,定义了Pythagorean梯形模糊语言加权算术平均算子,并给出了具体的表达形式;最后,以某个企业需要选择绿色供应商为实例,验证了Pythagorean梯形模糊语言加权算术平均算子在多属性群决策问题中的实用性和可行性。

Multiple attribute decision making method based on trapezoid fuzzy linguistic variables

The problem of multiple attribute decision making under fuzzy linguistic environments, in which decision makers can only provide their preferences （attribute values）in the form of trapezoid fuzzy linguistic variables（TFLV）, is studied. The formula of the degree of possibility between two TFLVs is defined, and some of its characteristics are studied. Based on the degree of possibility of fuzzy linguistic variables, an approach to ranking the decision alternatives in multiple attribute decision making with TFLV is developed. The trapezoid fuzzy linguistic weighted averaging （TFLWA） operator method is utilized to aggregate the decision information, and then all the alternatives are ranked by comparing the degree of possibility of TFLV. The method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision results reasonable and effective. Finally, the implementation process of the proposed method is illustrated and analyzed by a practical example.