A directional distance function approach to void the non-Archimedean in DEA
针对DEA模型中非阿基米德无穷小ε带来的计算困难，提出用方向距离函数避免选择或估计ε值，简化了模型应用。
Over the past years, the data envelopment analysis (DEA) methodology has registered widespread use among researchers from many fields. Furthermore, it is important to note that the non-Archimedean infinitesimal, ɛ, is a key concept in DEA models. Nevertheless, it is known that some computational difficulties arise when using ɛ in DEA. In this short communication, we show how the non-Archimedean may be voided using a directional distance function approach. Thus, our approach avoids choosing a real number (10−5 or 10−6) as a value for ɛ or estimating the same.