• 人工智能 •

### 基于多专家区间数的多属性群决策方法

1. 1.安徽大学 数学科学学院, 合肥 230039;
2.计算智能与信号处理教育部重点实验室(安徽大学), 合肥 230039
• 收稿日期:2011-08-17 修回日期:2011-12-09 发布日期:2012-03-01 出版日期:2012-03-01
• 通讯作者: 毛军军
• 作者简介:毛军军(1973-),女,浙江杭州人,副教授,博士,主要研究方向:智能计算、统计决策;王翠翠(1989-),女,安徽宿州人,硕士研究生,主要研究方向:不确定理论、多属性决策;姚登宝(1987-),男,安徽合肥人,硕士研究生,主要研究方向:概率统计。
• 基金资助:

国家自然科学基金资助项目(61073117);安徽大学学术创新团队项目(KJTD001B);安徽省高等学校青年基金资助项目(2011SQRL186)。

### Method for multi-attribute group decision-making based on multi-experts' interval numbers

MAO Jun-jun1,2, WANG Cui-cui1, YAO Deng-bao1

1. 1.School of Mathematical Sciences, Anhui University, Hefei Anhui 230039, China;
2.Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education (Anhui University), Hefei Anhui 230039, China
• Received:2011-08-17 Revised:2011-12-09 Online:2012-03-01 Published:2012-03-01

Abstract: A group decision-making method based on non-linear programming model was proposed for multi-attribute problem based on multi-experts' interval numbers. This method had constructed the following principles: under different objects and attribute conditions, the weight of an expert would be bigger if his evaluation value was close to the mean value of all experts' evaluation; on the other hand, smaller. Based on this, the problem that experts' weights were hard to be determined had been solved successfully with interval distance formula and programming model. According to aggregated operator theory, decision-making matrices had be aggregated into a collective decision-making matrix by use of interval weighted arithmetic aggregated operator, then aggregated into an overall attribute value by attribute weights, and with two-dimensions possibility degree, a possibility degree matrix had been constructed to rank all objects by ranking vectors method. Finally, a case study was presented to verify the proposed method's feasibility and rationality.