一种基于区间直觉梯形模糊数偏好的大群体决策冲突测度研究

中国管理科学 ›› 2014, Vol. 22 ›› Issue (8): 115-122.

一种基于区间直觉梯形模糊数偏好的大群体决策冲突测度研究

徐选华, 万奇锋, 陈晓红, 周艳菊

中南大学商学院, 湖南长沙 410083

收稿日期:2012-07-16 修回日期:2013-02-26 出版日期:2014-08-20 发布日期:2014-08-23
作者简介:徐选华（1962- ），男（汉族），江西临川人，中南大学商学院教授，博导，研究方向：决策理论与技术、信息系统与决策支持系统、工程管理.
基金资助:
国家自然科学基金资助项目（71171202，71171201）；国家创新研究群体科学基金资助项目（71221061）

Study for a Conflict Measure for Large Group Decision based on Interval-valued Intuitionistic Trapezoidal Fuzzy Number

XU Xuan-hua, WNA Qi-feng, CHEN Xiao-hong, ZHOU Yan-ju

School of Business, Central South University, Changsha 410083, China

Received:2012-07-16 Revised:2013-02-26 Online:2014-08-20 Published:2014-08-23

摘要/Abstract

摘要： 针对决策偏好为区间直觉梯形模糊数的大群体决策冲突测度问题，首先给出了两个区间直觉梯形模糊数的距离，提出了群体成员冲突函数，基于该函数对大群体成员偏好进行聚类形成若干聚集，以此为基础提出了聚集冲突测度模型并集结为群体冲突测度模型，然后应用于大群体偏好集结。最后通过一个算例对模型进行了验证。该模型便于大群体意见的分析与协调，适用于群决策支持系统，在应急决策中具有实际应用价值。

关键词: 区间直觉梯形模糊数, 大群体决策, 冲突测度

Abstract: Large group decision making is a difficult problem because it is hard to coordinate the conflict among multiple people. Conflict measure problems of large group are studied with every decision preferences expressed by interval-valued intuitionistic trapezoidal fuzzy number (IITFN). Firstly, the distance measurement between two IITFNs is given and conflict function among group members is proposed. Then, large group members are clustered. Afterwards, the cluster and group conflict measure models are proposed respectively and applied in the aggregating of large group preferences. Finally, a simulation example validates the model. This model deals with the analysis and coordination of large group decision, so it is applicable for group decision support system.

Key words: interval-valued intuitionistic trapezoidal fuzzy number, large group decision, conflict measure

中图分类号:

TP311.52

徐选华, 万奇锋, 陈晓红, 周艳菊. 一种基于区间直觉梯形模糊数偏好的大群体决策冲突测度研究[J]. 中国管理科学, 2014, 22(8): 115-122.

XU Xuan-hua, WNA Qi-feng, CHEN Xiao-hong, ZHOU Yan-ju. Study for a Conflict Measure for Large Group Decision based on Interval-valued Intuitionistic Trapezoidal Fuzzy Number[J]. Chinese Journal of Management Science, 2014, 22(8): 115-122.

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