基于直觉正态模糊信息集成的多属性决策

Intuitionist Normal Fuzzy Information Aggregation Operators and Their Applications to Multi-attribute Decision Making

在直觉正态模糊环境下,首先定义了直觉正态模糊数的新的运算法则,并探究了运算法则的性质;其次,提出了直觉正态模糊信息集成算子,包括直觉正态模糊加权平均算子和直觉正态模糊加权几何算子,并对新提出的两种算子间的大小进行比较;最后在新的信息集成算子基础上,提出了一种处理多属性决策问题的方法;结合区域经济发展研究实例,对提出的系统决策方法进行验证。测试结果表明,多属性决策方法是正确的、可行的与高效的。

In this paper, under the intuitionist normal fuzzy environment, new intuitionist normal fuzzy operational laws are defined and their properties are discussed. Then, the intuitionist normal fuzzy information aggregation operators are investigated, including intuitionist normal fuzzy weighted averaging operator(INFWA) and intuitionist normal fuzzy weighted geometric operator(INFWG). The relationship between these two operators is studied. In the end, based on these two proposed operators, we develop a new method to deal with the multi-attribute decision making problems under the intuitionist normal fuzzy environment, and then apply the presented method to the research on the development of the regional economy. The results obtained from the performance analysis show that our approach is correct, feasible and efficient.