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Convex cone-based ranking of decision-making units in DEA

机译:基于凸锥的DEA中决策单位的排名

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One of the major research streams in data envelopment analysis (DEA) is ranking decision-making units (DMUs). Utilizing a multicriteria decision-making technique, we develop a novel approach to fully rank all units. Motivated by the convex cone-based total order for multiple criteria alternatives proposed by Dehnokhalaji et al. (Nav Res Logist 61(2):155-163, 2014), we consider DMUs in DEA as multiple criteria alternatives and obtain their total ordering. Initially, some pairwise preference information is provided by the decision maker for units and the concepts of convex cones and polyhedral sets are defined in a DEA framework, correspondingly. We apply a modification of Dehnokhalaji et al. method to extract additional preference information for each pair of units and consequently obtain a full ranking (strict total ordering) of DMUs. The benefit of our approach to their method is that we apply non-radial models to overcome the instability drawback of radial models and their infeasibility occurring in DEA applications. The proposed approach is implemented for two numerical examples, and the accuracy of it is investigated through a computational test.
机译:数据包络分析(DEA)的主要研究流之一是对决策单位(DMU)进行排名。利用多准则决策技术,我们开发了一种新颖的方法来对所有单位进行完全排名。由Dehnokhalaji等人提出的基于凸锥的总阶为多个准则的替代动机。 (Nav Res Logist 61(2):155-163,2014),我们将DEA中的DMU视为多个标准替代方案,并获得其总排序。最初,决策者为单位提供一些成对的偏好信息,并且在DEA框架中相应地定义了凸锥和多面体集的概念。我们对Dehnokhalaji等进行了修改。提取每对单元的其他偏好信息并因此获得DMU完整排名(严格的总排序)的方法。我们对他们的方法的方法的好处是我们应用非径向模型来克服径向模型的不稳定性缺点以及它们在DEA应用程序中不可行的缺点。所提出的方法是通过两个数值示例实现的,并通过计算测试来研究其准确性。

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