考虑可信度和属性优先级的犹豫模糊决策方法

研究了考虑可信度的犹豫模糊混合集成因子以及考虑属性优先级的犹豫模糊多属性决策方法。首先给出了用于衡量数据差异程度的加权变异率公式,并证明了其具有类似于基尼系数的优良度量性质,之后在此基础上提出了可信度诱导犹豫模糊混合平均(CIHFHA)算子。针对属性权重信息未知的犹豫模糊决策问题,构建了一种新的考虑属性优先级的熵值修正G1的组合赋权方法,该方法可有效地利用属性客观评价数据以及通过考虑属性优先级体现专家意见,解决了主客观权重分配问题,得出的属性权重更加客观、合理。之后给出了一种基于CIHFHA算子和组合赋权方法的多属性决策方法,算例说明该方法的有效性和实用性。

Hesitant Fuzzy Decision Making Method with Confidence Levels and Preference Relations on Attributes

The multiple attribute decision making problem with confidence levels and preference information on attributes under hesitant fuzzy environment is studied. At first, we introduce a useful formula of weighed rate of variation for measuring data variation degree and shows the index of weighed rate of variation has good measuring characteristics like Gini coefficient. Then we put forward confidence induced hesitant fuzzy hybrid averaging(CIHFHA)operator based on the weighed rate of variation. According to the hesitant fuzzy multi-attribute decision making problem of unknown attribute weights information, we construct a new evaluation model of attributes weights called entropy correction group G1 combination weights with preference information on attributes. The method can effectively use the objective data of attributes and reflect the opinions of experts by considering the preference information on attributes. It also settles the allocation problem of subjective and objective determination problem, and makes the obtained attribute weights more objective and reasonable. Finally, a hesitant fuzzy multiple attribute decision making method based on CIHFHA operator and combination weights method is provided, and examples are given to illustrate the validity and practicability of the method.