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Group decision support methodology based upon the multigranular generalized orthopair 2-tuple linguistic information model
International Journal of Intelligent Systems ( IF 7 ) Pub Date : 2021-04-07 , DOI: 10.1002/int.22419
Ya Qin 1 , Yi Liu 1 , Saleem Abdullah 2 , Guiwu Wei 3
Affiliation  

In multiattribute group decision-making (MAGDM), experts often articulate their preference information to support decision-making by applying the multigranular linguistic model. Thus, the present work aims to introduce a novel MAGDM model to manage multigranular generalized orthopair 2-tuple linguistic information (GO2TLI). To begin with, a generalized orthopair 2-tuple linguistic model is put forward with the attempt of taking advantages of both q-rung orthopair fuzzy set (q-ROFS) and the 2-tuple linguistic model, while a transformation approach is supplied to tackle the consistency of multigranular GO2TLI. In addition, the Archimedean Copula as well as the Co-Copula operators are extended to handle GO2TLI along with their operational laws, to comprehensively model the relationship among attributes and experts. The Banzhaf Choquet-Copula aggregation operators on the generalized orthopair 2-tuple linguistic (GO2TLBCCA) are introduced, also some of its properties discussed. Third, the algorithms for regulating and determining the fuzzy measure (FM) of attributes and experts sets are proposed, followed by the corresponding decision-making approaches based upon the proposed GO2TLBCCA. The proposed MAGDM model can not only accommodate effectively the FMs of attribute (and expert) sets which are given subjectively, but also effectively address some multigranular GO2TLI as well as the partially unknown or completely unknown weights of attribute and expert sets. Finally, a case study is provided to demonstrate the validity of the proposed approach along with relevant discussions, the merits of the proposed approach are also analyzed by comparing with some extant decision methods.

中文翻译:

基于多粒度广义正射对二元组语言信息模型的群决策支持方法

在多属性群决策 (MAGDM) 中,专家经常通过应用多粒度语言模型阐明他们的偏好信息以支持决策。因此,目前的工作旨在引入一种新的 MAGDM 模型来管理多粒度广义 orthopair 2 元组语言信息 (GO2TLI)。首先,尝试利用q- rung orthopair模糊集( q-ROFS) 和 2-tuple 语言模型,同时提供了一种转换方法来解决多粒度 GO2TLI 的一致性问题。此外,阿基米德 Copula 以及 Co-Copula 算子被扩展到处理 GO2TLI 及其运算法则,以综合建模属性和专家之间的关系。介绍了广义正交对二元组语言 (GO2TLBCCA) 上的 Banzhaf Choquet-Copula 聚合算子,并讨论了它的一些性质。第三,提出了用于调节和确定属性和专家集的模糊测度(FM)的算法,然后是基于所提出的 GO2TLBCCA 的相应决策方法。所提出的 MAGDM 模型不仅可以有效地适应主观给出的属性(和专家)集的 FM,但也有效地解决了一些多粒度的 GO2TLI 以及属性和专家集的部分未知或完全未知的权重。最后,提供了一个案例研究来证明所提出方法的有效性以及相关讨论,并通过与一些现有决策方法进行比较来分析所提出方法的优点。
更新日期:2021-05-28
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