基于联系数的属性权重未知的三角模糊数多属性决策

Triangular Fuzzy Number Multi-attribute Decision-making with the Attribute Weight Unknown Based on Connection Number

针对属性权重完全未知且属性值为三角模糊数的多属性决策问题,采用属性值离差最大法确定属性权重,用"均值+偏差"联系数代表原属性值三角模糊数,按"均值"的加权求和模型得到方案的初排序,利用联系数中i的不同取值作排序不确定分析,应用概率统计原理综合不确定性分析结果,得到终排序,在提高决策可信性的同时,简化了属性权重完全未知的三角模糊数多属性建模与计算过程。实例表明新方法简明有效。

For the fuzzy multi-attribute decision making （FMADM） problems, in which the information about attribute weights are unknown completely and the attribute values are in the form triangular fuzzy numbers, a method based on connection number is proposed. The attribute weights unknown are calculated by the maximum deviation of the attribute values, and the attribute values with the triangular fuzzy numbers are converted into connection numbers with the form of ＂average ＋ deviation＂. Furthermore, a model based on the ＂average＂ model of weighted summation is built. On this, the plan at the beginning of the sequence is given, the sort of uncertainty is analyses by using the ＂i＂ different values of connection numbers, and then, the basis of the principle of probability and statistics integrated uncertainty as a result, get the final sorting. While improve the credibility of decision-making, simplifies the attribute weights is completely unknown of triangular fuzzy number multi-attribute modeling and calculation process. Examples show that the new method is concise and effective.