An acceptance system decision rule with data envelopment analysis

This paper further discusses the suggestion proposed by Troutt et al. that data envelopment analysis (DEA) can be used to develop an acceptance boundary. It is shown that the linear programming model with an arbitrary objective function developed by Troutt et al. can, in fact, be directly obtained from their assumptions. We develop a DEA-type linear programming model to determine not only whether a new case is accepted, but also the location of the new case with respect to the samples previously classified. A numerical example is provided.