Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to...

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

Data Envelopment Analysis (DEA) deals with evaluating a set of decision-making units (DMUs) based on nonparametric mathematical approaches. In classical DEA models, the given set of factors of DMUs is divided into two categories, inputs and outputs, while in some practical problems there are some measures whose membership to these categories is unclear. It means these factors treat different in...

data envelopment analysis (dea) is a mathematical programming-based approach for evaluates the relative efficiency of a set of dmus (decision making units). the relative efficiency of a dmu is the result of comparing the inputs and outputs of the dmu and those of other dmus in the pps (production possibility set). also, in data envelopment analysis various models have been developed in order to...

It is well established that multiple reference sets may occur for a decision making unit (DMU) in the non-radial DEA (data envelopment analysis) setting. As our first contribution, we differentiate between three types of reference set. First, we introduce the notion of unary reference set (URS) corresponding to a given projection of an evaluated DMU. The URS includes efficient DMUs that are act...

In this paper, we extend the standard data envelopment analysis (DEA) model to include longer term top management goals. This extension is in recognition of the fact that benchmarking for decision making units (DMUs) is more than a purely monitoring process, and includes a component of future planning. The new model uses a goal programming structure to find points on the efficient frontier whic...

Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to...

In this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. Our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. So, initially we find the interval changes of each input...

The traditional data envelopment analysis (DEA) models treat a decision making unit (DMU) as a “black box”, which is often criticized for not considering the inner production mechanism of a production system. The network DEA models developed to overcome this deficiency by considering the internal structure of a DMU have recently gained popularity. The inner data, however, are not generally avai...