基于新距离测度的对偶犹豫模糊TOPSIS方法

Dual Hesitant Fuzzy TOPSIS Method Based on Novel Distance Measure

研究了属性权重完全未知且对方案有偏好的对偶犹豫模糊多属性决策问题.首先,提出一种新的对偶犹豫模糊距离公式,无需人为添加元素,可直接进行计算.其次,基于新的距离公式,建立方案的主观偏好与客观偏好间偏差最小的属性权重优化模型,并将TOPSIS方法推广到对偶犹豫模糊环境下,对方案进行择优排序.最后,通过电力系统安全性评估的实例验证所提方法的可行性.

The dual hesitant fuzzy multiple attribute decision making problem with unknown weight information and preference information on alternatives is investigated.Firstly,a novel distance measure between two dual hesitant fuzzy sets that there is no need to add any values into the shorter dual hesitant fuzzy element is presented.Secondly,based on the proposed distance measure,a mathematical model for minimizing the total deviation between subjective and objective preference information on alternatives is constructed to obtain the attribute weights.Then the TOPSIS method is extended to accommodate dual hesitant fuzzy environment and the alternatives can be ranked.Finally,a numerical example on power system security assessment is given to verify the feasibility of the proposed method.