Data Envelopment Analysis (DEA) cannot provide adequate discrimination among efficient decision making units (DMUs). To discriminate these efficient DMUs is an interesting research subject. The purpose of this paper is to develop the mix integer linear model which was proposed by Foroughi (Foroughi A.A. A new mixed integer linear model for selecting the best decision making units in data envelo...

The mixed-integer linear programming data envelopment analysis models were proposed due to this reason that the conventional DEA models may suggest some non-integer values for the inputs and/or outputs of decision making units (DMUs) which those data can only be specified with integer values such as the number of employees and books. There are a few researches on integer-valued DEA and this pap...

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/ or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, ...

data envelopment analysis (dea) has been widely studied in the literature since its inception with charnes, cooper and rhodes work in 1978. the methodology behind the classical dea method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. one of the underlying assumptions of this methodology is that the units consume and prod...

Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception with Charnes, Cooper and Rhodes work in 1978. The methodology behind the classical DEA method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. One of the underlying assumptions of this methodology is that the units consume and prod...

We show how to implement the cross-validation technique used in machine learning as a slice model. We describe the formulation in terms of support vector machines and extend the GAMS/DEA interface to allow for efficient solutions of linear, mixed integer and simple quadratic slice models under GAMS.

The conventional data envelopment analysis (DEA) assumes that the inputs and outputs are real values. However, in many real world instances, some inputs and outputs must be in integer values. While integer-valued DEA models have been proposed, the current paper develops an integer-valued DEA super-efficiency model. Super-efficiency DEA models are known to have the problem of infeasibility. Rece...

Conventional data envelopment analysis (DEA) models normally assume all inputs and outputs are real valued and continuous. However in problems some inputs and outputs can only take integer values, also, both desirable and undesirable outputs can be generated . In this paper the effect of undesirable outputs in integer DEA model is discussed. The proposed model distinguishes weak disposability o...

When organizations do not have well defined goals and constraints, traditional mixed integer programming MIP models are ineffective for portfolio selection. In such cases, some organizations revert to building project portfolios based on data envelopment analysis DEA relative efficiency scores. However, implementing the k most efficient projects until resources are expended will not always resu...