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Measurement of overall performances of decision-making units using ideal and anti-ideal decision-making units

机译:使用理想和反理想决策单位衡量决策单位的整体绩效

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Data envelopment analysis (DEA) is a method for evaluating relative efficiencies of decision-making units (DMUs) which perform similar functions in a production system, consuming multiple inputs to produce multiple outputs. The conventional form of DEA evaluates performances of DMUs only from the optimistic point of view. In other words, it chooses the most favorable weights for each DMU. There is another approach that measures efficiency of a DMU from the pessimistic point of view. This approach chooses the most unfavorable weights for evaluation of each DMU. In this paper, we propose to integrate both efficiencies in the form of an interval in order to measure the overall performance of a DMU. The proposed DEA models for evaluation of efficiencies are called bounded DEA models. The proposed approach will be compared using a numerical example. Another example regarding performance evaluation of 50 bank branches in Iranian cities will be presented to demonstrate the advantages, simplicity, and utility of this approach in real-life situations.
机译:数据包络分析(DEA)是一种评估决策单位(DMU)相对效率的方法,决策单位在生产系统中执行相似的功能,消耗多个输入以产生多个输出。 DEA的传统形式仅从乐观的角度评估DMU的性能。换句话说,它为每个DMU选择最有利的权重。还有一种从悲观的角度衡量DMU效率的方法。此方法选择最不利的权重来评估每个DMU。在本文中,我们建议以间隔的形式整合这两种效率,以衡量DMU的整体性能。提出的用于评估效率的DEA模型称为有界DEA模型。所提出的方法将通过一个数值示例进行比较。还将提供有关在伊朗城市的50家银行分支机构进行绩效评估的另一个示例,以证明该方法在现实生活中的优势,简便性和实用性。

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