多粒度支持直觉模糊粗糙集的多属性决策方法

针对多属性决策中多个相互冲突的属性信息使决策者很难做出决策判断的问题,文中从支持直觉模糊集的角度研究该问题.首先,在支持直觉模糊集的基础上,结合多粒度粗糙集理论,构造乐观、悲观两种多粒度支持直觉模糊粗糙集模型,分析两种模型之间的相互关系,讨论相关性质.然后,利用t-模和t-余模定义拟合函数,提出多粒度支持直觉模糊粗糙集的多属性决策求解方法,同时定义得分函数和精确函数排序决策结果,提取相应的决策规则,设计算法.实例分析表明,文中方法使决策者在处理信息冲突的多属性决策问题时可根据实际需求选择最优决策方案.

Multi-attribute Decision-Making Method Based on Multi-granulation Support Intuitionistic Fuzzy Rough Sets

Multiple contradictory attribute information makes it difficult for decision makers to make decisions in multi-attribute decision-making, and therefore the problem are studied from the perspective of support intuitionistic fuzzy sets in this paper. Firstly, on the basis of support intuitionistic fuzzy sets, two models of optimistic and pessimistic multi-granulation support intuitionistic fuzzy rough sets are constructed in combination with the theory of multi-granulation rough sets. The relationship between two models above is analyzed and the related properties are discussed. Then, the fitting function is defined by t-norm and t-conorm, and a multi-attribute decision-making solving method with multi-granulation support intuitionistic fuzzy rough sets is proposed. Meanwhile, a score function and a accuracy function are defined to sort decision results, the corresponding decision rules are extracted, and an algorithm is designed. Example analysis verifies that the method enables decision makers to select the optimal decision-making scheme according to actual demands while dealing with conflicting multi-attribute decision-making problems.