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Uncertain random data envelopment analysis for technical efficiency
Fuzzy Optimization and Decision Making ( IF 4.7 ) Pub Date : 2021-04-05 , DOI: 10.1007/s10700-021-09361-0
Bao Jiang , Wenxue Feng , Jian Li

Data envelopment analysis (DEA) is a classical and prevailing tool for estimating relative efficiencies of multiple decision making units (DMUs). However, sometimes DMUs’ inputs and outputs cannot be observed accurately in practical cases, and hence this paper attempts to propose an uncertain random DEA model to evaluate the efficiencies of DMUs with uncertain random inputs and outputs. The sensitivity and stability of this new model are further analyzed with the aim to figure out the stability radius of each DMU. Finally, a numerical example is presented for illustrating the proposed uncertain random DEA model.



中文翻译:

不确定的随机数据包络分析以提高技术效率

数据包络分析(DEA)是一种经典且流行的工具,用于估计多个决策单位(DMU)的相对效率。然而,有时在实际情况下不能准确地观察到DMU的输入和输出,因此本文试图提出一种不确定的随机DEA模型,以评估具有不确定的随机输入和输出的DMU的效率。为了确定每个DMU的稳定半径,进一步分析了该新模型的灵敏度和稳定性。最后,给出了一个数值示例来说明所提出的不确定随机DEA模型。

更新日期:2021-04-05
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