离差最大化时基于交叉评价的多属性决策方法

针对属性权重完全未知,且评价系统内既有客观数据、又有主观因素的多属性决策问题,提出一种基于离差最大化和交叉评价的模糊多属性决策方法。该方法首先定义了最小交叉效率、最大交叉效率等概念,将量化指标用交叉评价方法进行处理;然后采用模糊综合评价方法评价非量化指标,并基于离差最大化思想确定权重;最后将模糊化处理之后的量化指标与非量化指标一起进行最终评价,建立离差最大化条件下基于交叉评价的模糊多属性决策模型。最后通过算例验证了方法的可行性及有效性。

Fuzzy Multi-attribute Decision Making Method Based on MaximizingDeviation and Cross-Evaluation

Considering the multi-attribute decision making problem with both quantitative data and non quantitative index, in which the information about attribute weights are unknown completely, a method based on maximizing deviation and cross-evaluation is introduced. First we calculate the “average cross-efficiency evaluation”, “minimum cross-efficiency evaluation”, “maximum cross-efficiency evaluation” using the cross-evaluation model; then use the fuzzy comprehensive evaluation model to deal with the non quantitative index; finally we evaluate the quantitative data and non quantitative index together. The weight of every decision unit is determined by the maximizing deviation method. And an example is given to illustrate the effectiveness of the method proposed.