权重信息不完全的二元语义多属性群决策方法

针对解决具有语言评价信息的多属性群决策问题,提出了一种基于最大偏差和二元语义信息处理的群决策方法。该方法是采用近年来最新发展的二元语义概念对语言评价信息进行处理和运算。对于属性权重完全未知或属性权重信息不完全的情形,分别给出了一个求解属性权重的简洁公式和一个基于最大偏差的目标规划模型,分别获得相应的属性权重,然后利用二元语义加权算术平均(T-WAA)算子,对二元语义决策信息进行加权集成,继而对决策方案进行排序和择优。该方法具有对语言信息处理较为精确的特点,避免了以往采用的语言信息处理方法所带来的信息扭曲和损失。最后给出了一个实例分析。结果表明该方法简单,有效和易于计算。

Two-tuple linguistic multiple attribute group decision making with incomplete attribute weight information

With respect to multiple attribute group decision making problems with linguistic assessment information,a new method based on maximizing deviation and two-tuple is proposed.In this method,the two-tuple linguistic representation developed in recent years is used to aggregate the linguistic assessment information.An optimization model based on the maximizing deviation method,by which the attribute weights can be determined,is established.For the special situations where the information about attribute weights is completely unknown,another optimization model is established.By solving this model,a simple and exact formula can be used to determine the attribute weights.The two-tuple linguistic weighting arithmetic average(T-WAA) operator is utilized to aggregate the linguistic information corresponding to each alternative in order to rank the alternatives and select the most desirable one(s).This method has exact characteristic in linguistic information processing,so that the information distortion and losing which occur formerly in the linguistic information processing are avoided. Finally,a numerical example is used to illustrate the approach is simple,effective and easy to calculate.