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Restricting the relative weights in data envelopment analysis

机译:限制数据包络分析中的相对权重

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In this paper, we address the problem of relative weight restriction in data envelopment analysis (DEA). A fuzzy-based approach to restricting the relative weights is proposed in this study. Unlike the classical weight restriction methods, the proposed approach has an interactive orientation. That is, similar to analytical hierarchy process, the proposed method shares the decision maker (DM) in weight restriction process. Here, the preferences of DM are asked via pairwise comparison matrices. Then, the weights of factors (inputs/outputs) are extracted from these matrices. These weights, finally, are incorporated in multiplier DEA models as the parametric triangular fuzzy numbers, in which, the parameter value indicates the degree of conformity of the relative weights according to DM views. To best of our knowledge, no one has been yet utilized fuzzy set theory to control the relative weights in DEA. Putting in another word, the contribution of this study is that the authors propose a new approach based on fuzzy set theory to weight restriction in DEA. A last, a real case on financial banking efficiency is used to illustrate the proposed approach.
机译:在本文中,我们解决了数据包络分析中相对体重限制的问题(DEA)。在本研究中提出了一种基于模糊的限制相对重量的方法。与古典重量限制方法不同,所提出的方法具有互动方向。也就是说,类似于分析层次结构,所提出的方法共享重量限制过程中的决策者(DM)。这里,通过成对比较矩阵询问DM的偏好。然后,从这些矩阵中提取因子(输入/输出)的权重。最后,这些权重被包含在乘法器DEA模型中,作为参数三角模糊数,其中参数值指示根据DM视图的相对权重的概括程度。尽量众所周知,没有人已经使用过模糊集合理论来控制DEA中的相对重量。换句话说,本研究的贡献是提交人提出了一种基于模糊集理论的新方法,以便在DEA中的体重限制。最后一个关于金融银行效率的真正案例用于说明所提出的方法。

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