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Pythagorean linguistic preference relations and their applications to group decision making using group recommendations based on consistency matrices and feedback mechanism

机译:佩达哥兰语言偏好关系及其在基于一致性矩阵和反馈机制的组建议对决策的应用

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In this paper, we introduce a new type of fuzzy set, called Pythagorean linguistic sets (PLSs), to address the preferred and nonpreferred degrees of linguistic variables. Moreover, it allows decision makers to offer effectively handle uncertain information more flexible than intuitionistic linguistic sets (ILSs) when one compares two alternatives in the process of decision making. Some of the fundamental operational laws, score, accuracy, and aggregation operators are defined, and their properties are investigated. Preference relation (PR) is a useful and efficient tool for decision making that only requires the decision makers to compare two alternatives at one time. Taking the advantages of PLSs and PRs, this paper also introduces Pythagorean linguistic preference relations (PLPRs) and studies their application. We propose an approach for group decision making using group recommendations based on consistency matrices and feedback mechanism. First, the proposed method constructs the collective consistency matrix, the weight collective PRs, and the group collective PRs. Then, it constructs a consensus relation for each expert and determines the group consensus degree (GCD) for all experts. If the GCD is smaller than a predefined threshold value, then a feedback mechanism is activated to update the PLPRs. Finally, after the GCD is greater than or equal to the predefined threshold value, we calculate the arithmetic mathematical average values of the updated group collective PR to select the most appropriate alternative.
机译:在本文中,我们介绍了一种新型的模糊集,称为Pythagorean语言集(PLSS),以解决优选的和非专利的语言变量。此外,它允许决策者在一个比较决策过程中的两个替代方案时,有效地处理比直觉语言集(ILSS)更灵活的信息。定义了一些基本操作法律,得分,准确性和聚合运营商,并调查了其性质。偏好关系(PR)是一个有用而有效的工具,用于决策,只需要决策者一次比较两个替代方案。采取PLSS和PRS的优势,本文还介绍了毕达哥兰语言偏好关系(PLPRS)并研究其应用。我们提出了一种使用基于一致性矩阵和反馈机制的组建议的组决策方法。首先,所提出的方法构建集体一致性矩阵,重量集体PRS和组集体PRS。然后,它构建了每个专家的共识关系,并确定所有专家的团体共识(GCD)。如果GCD小于预定义的阈值,则激活反馈机制以更新PLPR。最后,在GCD大于或等于预定义的阈值之后,我们计算更新的组集体PR的算术数学平均值,以选择最合适的替代。

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