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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >A novel approach to multi-attribute group decision making based on q-rung orthopair uncertain linguistic information
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A novel approach to multi-attribute group decision making based on q-rung orthopair uncertain linguistic information

机译:基于Q-rsg orthopair不确定语言信息的多属性组决策的一种新方法

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The recently proposed q-rung orthopair fuzzy set (q-ROFS) is an effective tool for handling fuzziness and uncertainty in the process of multi-attribute group decision making (MAGDM). Considering that in most MAGDM problems, not only decision makers' quantitative evaluation information but also their qualitative assessment opinions should be taken into account, this paper proposes a concept of q-rung orthopair uncertain linguistic sets (q-ROULSs) by combining q-ROFS s with uncertain linguistic variables (ULVs). The proposed q-ROULSs parallel to intuitionistic uncertain linguistic sets (IULSs) and Pythagorean uncertain linguistic sets (PULSs), but provide more freedom for decision makers to express their evaluation information. Afterwards, we propose operational laws and a comparison law for q-ROULSs. To effectively aggregate q-rung orthopair uncertain linguistic information, we extend the Muirhead mean (MM) operator to q-ROULSs and propose a family of q-rung orthopair uncertain linguistic Muirhead mean operators. The prominent advantage of the proposed operators is that the interrelationship among any numbers of input arguments can be captured. In addition, some desirable properties and special cases of the proposed operators are studied. Moreover, we propose a new method to MAGDM problems based on the proposed operators within q-rung orthopair uncertain linguistic context. Finally, we conduct a numerical experiment to demonstrate the validity and superiorities of the proposed method.
机译:最近提出的Q-RONG Orthopair模糊套装(Q-ROF)是在多属性组决策(MAGDM)过程中处理模糊性和不确定性的有效工具。考虑到在大多数MAGDM问题中,不仅应考虑到决策者的定量评估信息,而且还应考虑到它们的定性评估意见,通过组合Q-ROF,提出了Q-rsg Ortopair不确定语言集(Q-Roulss)的概念s与不确定的语言变量(ULV)。所提出的Q-routss平行于直觉不确定语言集(Iulss)和毕达哥兰不确定语言集(豆类),但为决策者提供更多自由来表达他们的评估信息。之后,我们提出了Q-routss的运作法律和比较法。为了有效地聚集Q-rsg orthopair不确定的语言信息,我们将Muirhead均值(mm)操作员扩展到Q-routss,并提出了一个Q-rsg orthopair不确定语言学Muirhead均值均值均值均衡器。所提出的运营商的突出优势在于可以捕获任何数量的输入参数之间的相互关系。此外,研究了拟议的操作员的一些理想的性能和特殊情况。此外,我们提出了一种基于Q-Rung ortopail不确定语言背景下的提议的运营商的MAGDM问题的新方法。最后,我们进行数值实验,以证明所提出的方法的有效性和优越性。

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