Abstract Some input-output classifier data envelopment analysis (DEA) models in multiplier and envelopment forms were developed to designate the status of flexible measures, playing either input or output roles. These models ignore the role of non-Archimedean epsilon in the input-output classification process. We show that these epsilon-free models may ignore some flexible measures in the performance evaluation process and hence the status of such flexible measure(s) can be randomly and inappropriately identified. To fill this gap, we develop a pair of epsilon-based multiplier and envelopment classifier models. We also develop an approach to find a suitable epsilon value for our developed classifier models. A case study of the supplier selection problem in the Iranian Space Research Center (ISRC) is provided to illustrate the potential application of our new epsilon-based approach.

中文翻译：

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用于对灵活度量进行分类的新数据包络分析模型：非阿基米德 epsilon 的作用

摘要 开发了一些乘数和包络形式的输入-输出分类器数据包络分析（DEA）模型来指定灵活度量的状态，扮演输入或输出角色。这些模型忽略了非阿基米德 epsilon 在输入输出分类过程中的作用。我们表明，这些无 epsilon 模型可能会忽略绩效评估过程中的一些灵活措施，因此可以随机且不恰当地识别此类灵活措施的状态。为了填补这一空白，我们开发了一对基于 epsilon 的乘法器和包络分类器模型。我们还开发了一种方法来为我们开发的分类器模型找到合适的 epsilon 值。