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A Method of Multiple Attribute Group Decision Making Based on 2-Tuple Linguistic Dependent Maclaurin Symmetric Mean Operators

机译:一种基于2元组语言依赖性Maclaurin对称均衡器的多个属性组决策方法

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摘要

Aiming at multiple attribute group decision making (MAGDM) problems, especially the attribute values of 2-tuple linguistic numbers and the interrelationships between each attribute needing to be considered, this paper proposes a new method of analysis. Firstly, we developed a few new aggregation operators, like the 2-tuple linguistic dependent weighted Maclaurin symmetric mean (2TLDWMSM) operator, the 2-tuple linguistic dependent weighted generalized Maclaurin symmetric mean (2TLDWGMSM) operator, and the 2-tuple linguistic dependent weighted geometric Maclaurin symmetric mean (2TLDWGeoMSM) operator. In the above operators, Maclaurin symmetric mean (MSM) operators can take the relationships between each attribute into account and dependent operators can mitigate the unfair parameters’ impact on the overall outcome, in which those ‘‘incorrect’’ and ‘‘prejudiced’’ parameters are distributed with low weights. Next, a method used by the 2TLDWMSM, 2TLDWGMSM, and 2TLDWGeoMSM operators for MAGDM is introduced. Finally, there is an explanative example to confirm the proposed approach and explain its availability and usefulness.
机译:针对多个属性组决策制定(MAGDM)问题,特别是2元组语言数字的属性值以及需要考虑每个属性之间的相互关系,本文提出了一种新的分析方法。首先,我们开发了一些新的聚合运营商,如2元组语言依赖加权宏remmetric均值(2tldwmsm)运算符,2元组语言依赖性加权宏revery maclaurin对称均值(2tldwgmsm)运算符,以及2元组语言依赖权重几何Maclaurin对称平均值(2TLDWGEOMSM)操作员。在上面的运算符中,Maclaurin对称均值(MSM)运营商可以将每个属性与帐户之间的关系带到帐户,依赖的运营商可以减轻不公平的参数对整体结果的影响,其中“不正确”和“偏见”的影响参数分布低重量。接下来,介绍了2TLDWMSM,2TLDWGMSM和MAGDM的2TLDWGEOMSM运算符使用的方法。最后,有一个解释示例,以确认所提出的方法并解释其可用性和有用性。

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