Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (20): 218-222.

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Multi-attribute decision-making method of ITFN based on cross-entropy

FU Yanan1, MAO Junjun1,2, XU Danqing1   

  1. 1.School of Mathematical Sciences, Anhui University, Hefei 230601, China
    2.Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education, Anhui University, Hefei 230039, China
  • Online:2014-10-15 Published:2014-10-28

基于交叉熵的ITFN的多属性决策方法

付亚男1,毛军军1,2,徐丹青1   

  1. 1.安徽大学 数学科学学院,合肥 230601
    2.安徽大学 计算智能与信号处理教育部重点实验室,合肥 230039

Abstract: Focus on the problem of multi-attribute decision making, in which the attribute is the intuitionistic trapezoidal fuzzy number and the attribute weight information is complete unknown, a decision method is presented based on cross-entropy. The transformation approach between intuitionistic trapezoidal fuzzy number and intuitionistic fuzzy number is given by expectancy method, cross-entropy and relevant propositions are proposed. Based on the principle of minimizing the total discrimination information between every object and the positive ideal object, the formula of attribute weights is introduced by constructing non-linear programming model, thereby the attribute weight is determined. The example analysis shows the effectiveness of the method.

Key words: intuitionistic trapezoidal fuzzy number, multi-attribute decision making, cross-entropy, intuitionistic fuzzy number, positive ideal object, weight

摘要: 针对属性值为直觉梯形模糊数且属性权重完全未知的多属性决策问题,提出了一种基于交叉熵的决策方法。给出期望值的方法将直觉梯形模糊数转化为直觉模糊数,进而提出直觉模糊数的交叉熵等概念及相关性质。基于各方案与正理想方案的总区别信息最小化原则,建立非线性模型,求出属性权重。用实例说明该方法的有效性。

关键词: 直觉梯形模糊数, 多属性决策, 交叉熵, 直觉模糊数, 正理想, 权重