Abstract: To deal with multi-attribute decision making (MADM) problems with intuitionistic uncertain linguistic variables (IULVs), a MADM method is proposed to capture the interrelationship among multi-inputs and satisfy different semantic transformation requirements. First, considering the lack of closeness and flexibility of existing operational rules, some new operational rules and ranking method for IULVsare developed by combining the concept of linguistic scale function. Then, based on these new operations, the intuitionistic uncertain linguistic Hamy mean (IULHAM) operator and its weighted version (IULWHAM) are proposed to aggregate IULVs, which can model the interrelationship among multi-inputs. Meanwhile, some of desirable properties and special cases of the proposed operators are studied and discussed. Furthermore, a new MADM method with IULVs is proposed based on the proposed IULWHAM operator. Finally, an illustrative example is conducted to show the validity and discuss the advantages of the proposed method by comparing with other existing MADM methods with IULVs.

Key words: intuitionistic uncertain linguistic variable, Hamy mean operator, linguistic scale function, multi-attribute decision making method

摘要： 针对属性值为直觉不确定语言变量的多属性决策问题,提出一种不仅可以捕获属性间的多元关联关系并且能够满足决策者不同语义转换需求的多属性决策方法。首先,考虑已有运算法则缺少封闭性和灵活性,结合语言刻度函数,提出一种新的直觉不确定语言变量运算法则和排序方法。其次,根据新的运算法则,提出可以捕获属性间多元关联关系的直觉不确定语言Hamy平均及其加权形式,并对新算子的优良性质和特例进行了探讨和分析。进而,提出一种新的多属性决策方法。最后,通过算例和对比分析验证了该方法的有效性和优越性。

关键词: 直觉不确定语言变量, Hamy平均算子, 语言刻度函数, 多属性决策方法