Efficient DMUs improvement based on input expenses reduction using data envelopment analysis

Data Envelopment Analysis with Nonhomogeneous DMUs

Data envelopment analysis (DEA), as originally proposed, is a methodology for evaluating the relative efficiencies of a set of homogeneous decision-making units (DMUs) in the sense that each uses the same input and output measures (in varying amounts from one DMU to another). In some situations, however, the assumption of homogeneity among DMUs may not apply. As an example, consider the case wh...

Efficient location by using data envelopment analysis

So far, many types of location models have been developed to find optimal spatial patterns according to different spatial metrics such as cost, coverage and availability.  The initial focus of these models is on the location availability of service providers and demand estimates, and some of these models are within the framework of multi-objective programming models.  After the advent of scienc...

Finding Outlier DMUs in Data Envelopment Analysis

Calculating Super Efficiency of DMUs for Ranking Units in Data Envelopment Analysis Based on SBM Model

There are a number of methods for ranking decision making units (DMUs), among which calculating super efficiency and then ranking the units based on the obtained amount of super efficiency are both valid and efficient. Since most of the proposed models do not provide the projection of Pareto efficiency, a model is developed and presented through this paper based on which in the projection of Pa...

An improved approach to find and rank BCC-efficient DMUs in data envelopment analysis (DEA)

Recently, a mixed integer data envelopment analysis (DEA) model has been proposed to find the most BCC-efficient (or the best) decision making unit (DMU) by Toloo (2012). This paper shows that the model may be infeasible in some cases, and when the model is feasible, it may fail to identify the most efficient DMU, correctly. We develop an improved model to find the most BCC-efficient DMU that r...

Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis

During the last years, the concept of input congestion and technical ineff-ciency in data envelopment analysis (DEA), have been investigated by manyresearchers. The motivation of this paper is to present models which obtain thedecreased output value due to input congestion and technical ineciency. More-over, we extend the models to estimate input congestion, technical ineciencyand output reduct...