梯形区间二型模糊群决策发生算法及其综合比较法

Interval Type-2 Trapezoidal Fuzzy Number Group Decision-making Generator Algorithm and Systematic Comparison Method

针对高度不确定环境下的多准则群体决策问题,提出一种基于梯形区间二型模糊的多重处理隶属函数中模糊不确定信息的群决策综合比较法.首先,利用群决策发生算法处理个体决策的聚合问题;其次,利用改进的重心比较法和区域截集法分别处理隶属函数中隶属程度问题和模糊不确定程度问题;最后,根据对隶属函数的处理结果得到综合比较计分值并作为方案选择的依据.通过对隶属函数的主隶属区域和模糊不确定的离散区域的双重挖掘,并以不同数量级形式记录在结果中,使得该决策方法更加契合人类决策行为、决策结果更加真实有效、决策风险更小.文末通过实例分析和比较,证明了本文提出方法的可行性和有效性.

A group decision systematic comparison method for multiple processing fuzzy uncertain information in membership function based on interval type-2 trapezoidal fuzzy number is proposed for multiple criteria group decision making problems in highly uncertain environment. Firstly,we use the group decision-making generator algorithm to deal with the aggregation problem of individual decisionmaking information. Secondly,we use the improved center-of-gravity comparison method and the area cut sets method to deal with the membership degree problem and the fuzzy uncertainty degree in the membership function respectively. Finally,according to the processing results of membership function get systematic comparison score value and as a basis for the scheme selection. Through the double space data mining of the membership degree information and the vagueness and uncertainty degree information of the membership function,and recorded in the form of different orders of magnitude in the results,the decision-making method is more suitable for human decision-making behavior,and the decision result is more real and effective. At the end of this paper,the feasibility and validity of the proposed method are proved by a case analysis and comparison.