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A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

机译：基于云模型的具有二元组语言信息的多准则群决策方法

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This paper presents a new approach to solve the multi-criteria group decision making (MCGDM) problem where criteria values take the form of 2-tuple linguistic information. Firstly, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is proposed, which synthetically considers the importance of both individual and the ordered position so as to overcome the defects of existing operators. Secondly, combining the advantages of the cloud model and 2-tuple linguistic variable, a new generating cloud method is proposed to transform 2-tuple linguistic variables into clouds. Thirdly, we further define some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the criteria weights. Furthermore, a new approach for 2-tuple linguistic group decision making is presented on the basis of the THOWG operator, the improved generating cloud method as well as the new cloud algorithms. Finally, an example of assessing the social effects of biomass power plants (BPPS) is illustrated to verify the application and feasible of the developed approach, and a comparative analysis is also conducted to validate the effectiveness of the proposed method.
机译：本文提出了一种新的方法来解决多准则组决策（MCGDM）问题，其中准则值采用2元组语言信息的形式。首先，提出了一种二元混合有序加权几何算子，它综合考虑了个体和有序位置的重要性，克服了现有算子的缺陷。其次，结合云模型和2元组语言变量的优点，提出了一种新的生成云方法，将2元组语言变量转换为云。第三，我们进一步定义了一些新的云算法，例如云可能性度和云支持度，可以分别用来比较云并确定标准权重。此外，基于THOWG算子，改进的生成云方法以及新的云算法，提出了一种用于二元语言组决策的新方法。最后，以评估生物质能发电厂（BPPS）的社会效应为例，验证了该方法的应用和可行性，并进行了比较分析，验证了该方法的有效性。

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