基于粒计算的犹豫模糊多准则决策方法*

提出基于粒计算的犹豫模糊多准则决策方法.给出各个准则下对应的犹豫模糊集中犹豫模糊元的大于可能度定义，并构造相应准则下的加性一致的模糊偏好矩阵.根据各准则的模糊偏好矩阵对应的预序熵及预序粒结构相似度确定属性的权重，对各个准则下模糊偏好矩阵的排序向量加权平均得到最终的排序向量.文中方法以评价数据序信息量及准则序与整体之间的关系确定准则权重，通过计算加权两两比较下的排序向量得到最终的排序决策结果.最后运用实例验证算法的有效性及可行性.

Granular Computing Based Hesitant Fuzzy Multi-criteria Decision Making

A multi-criteria decision making method is proposed based on granular computing in hesitant fuzzy setting. Firstly, the possibility degree is defined for comparing hesitant fuzzy elements in a hesitant fuzzy set and an additive consistent fuzzy preference matrix is constructed based on the defined possibility degrees. Secondly, the criteria weights are determined by the preorder entropies and the similarity degree of preorder granular structures. Thirdly, an ordered vector is obtained by integrating the corresponding fuzzy preference matrices with the criteria weights. The criteria weights are computed from the evaluation information content and the relations between orders of the individual criteria and the whole evaluation system. The final ranking is obtained by weighting the ranking order under each criterion. Finally, a case study is utilized to verify the effectiveness and feasibility of the proposed method.