| 方案有不确定偏好的区间数相对熵群决策方法 |
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| 引用本文： | 刘小弟,朱建军,刘思峰.方案有不确定偏好的区间数相对熵群决策方法[J].中国管理科学,2014,22(6):134-140. |
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| 作者姓名： | 刘小弟 朱建军 刘思峰 |
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| 作者单位： | 1. 南京航空航天大学经济与管理学院, 江苏 南京 211106;
2. 安徽工业大学数理学院, 安徽 马鞍山 243002 |
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| 基金项目： | 国家自然科学基金资助项目（71171112）；江苏省高校哲学社会科学重点项目（2012ZDIXM007）；江苏省高校哲学社会科学重点研究基地重大项目（2012JDXM003）；中央高校基本科研业务费专项资金（NS2014086）；江苏省普通高校研究生科研创新计划项目（CXLX13_171）；广义虚拟经济研究专项（GX2013-1017CM）；安徽工业大学青年教师科研基金资助课题（QZ201321） |
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| 摘 要： | 研究了属性值是区间数并且已知方案偏好信息的多属性群决策问题。建立了每个方案客观偏好值与主观偏好值偏差的相对熵测度矩阵；基于客观信息和方案偏好信息的相对熵建立了属性权重模型；建立了一个新的区间数比较的可能度公式，基于可能度公式给出了方案排序方法，算例说明方法可行性。
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| 关 键 词： | 群决策 区间数 相对熵 可能度 |
| 收稿时间： | 2012-10-26 |
| 修稿时间： | 2013-03-25 |
Group Decision-Making Method with Uncertain Preference Information on Alternatives by Interval Number Relative Entropy |
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| LIU Xiao-di,ZHU Jian-jun,LIU Si-feng.Group Decision-Making Method with Uncertain Preference Information on Alternatives by Interval Number Relative Entropy[J].Chinese Journal of Management Science,2014,22(6):134-140. |
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| Authors: | LIU Xiao-di ZHU Jian-jun LIU Si-feng |
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| Institution: | 1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
2. School of Mathematics and Physics, Anhui University of Technology, Ma'anshan 243002, China |
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| Abstract: | The problem of multiple attribute group decision making with interval numbers and preference information on alternatives is studied in this paper. Firstly,he relative entropy matrix for the deviation between objective preference and subjective preference value on each alternative is obtained. Then a mathematical model based on the relative entropy of objective and preference information on alternatives is constructed to obtain the attribute weights. Furthermore,a new probability degree formula for the comparison between two interval numbers is presented. Based on the formula, a method for ranking alternatives is given. Finally, a numerical example is given to verify the proposed method and to demonstrate its feasibility. |
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| Keywords: | group decision-making interval number relative entropy probability degree |
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