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An optimization-based method for eliciting priorities from fuzzy preference relations with a novel consistency index

机译:一种基于优化的模糊偏好关系优先级引出具有新型一致性指数的方法

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摘要

Abstract Preference relations could be originated from a decision making problem by pairwisely comparing a finite set of alternatives. In order to find an optimal solution, a feasible approach is to elicit the priorities from the derived preference relation. In this paper, we report an optimization-based approach to the priorities elicited from fuzzy preference relations (FPRs). The inherent relation between row/column vectors of FPRs with additive/multiplicative consistency is considered. Under additive consistency, the variance-based additive consistency index (VACI) of FPRs is constructed and some properties are studied. With the knowledge of multiplicative consistency, the concept of transformation-based multiplicative consistency index is proposed. Using numerical simulations, the thresholds of the proposed consistency indexes for FPRs with acceptable additive/multiplicative consistency are determined. A new method for deriving the priority vector from FPRs is proposed by constructing an optimization problem. The optimal solution is studied and some comparisons with the existing methods are made. Finally, numerical examples are carried out to show the effectiveness of the proposed approach.
机译:摘要 偏好关系可以通过成对比较一组有限的备选方案来产生决策问题。为了找到最优解,一种可行的方法是从派生的偏好关系中引出优先级。在本文中,我们报告了一种基于优化的方法,用于处理从模糊偏好关系(FPR)中引出的优先级。考虑了FPRs的行/列向量与加法/乘法一致性之间的内在关系。在加性一致性下,构建了FPRs基于方差的加性一致性指数(VACI),并对其性质进行了研究。在了解乘法一致性的基础上,提出了基于变换的乘法一致性指数的概念。通过数值模拟,确定了具有可接受的加法/乘法一致性的FPRs的一致性指标阈值。通过构造优化问题,提出了一种从FPRs中推导优先级向量的新方法。研究了最优解,并与现有方法进行了比较。最后,通过数值算例验证了所提方法的有效性。

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