recently the concept of facility efficiency, which defined by data envelopment analysis (dea), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. by combining the dea models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

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...

background: during the last decades, the number of dentistry units increased significantly across the country. the aim of this study was to assess the efficiency of dental units of iran provinces regarding dental health inputs and outputs using data envelopment analysis approach. methods: in this applied descriptive-analytical study, the study population included all of iran 31 provinces. the o...

In a relatively short period of time Data Envelopment Analysis (DEA) has grown into a powerful quantitative, analytical tool for measuring and evaluating performance. DEA has been successfully applied to a host of different types of entities engaged in a wide variety of activities in many contexts worldwide. This chapter discusses the fundamental DEA models and some of their extensions.

The theory for measuring efficiency of producers has developed alternative approaches to include the effect of non-discretionary variables in the analysis. A review of different options in the specific literature of Data Envelopment Analysis (DEA) allows us to identify three main approaches: one-stage, two-stage and multi-stage models. Recently, some of these models have been improved through t...

In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit(DMU) in the best light in comparison to all the other DMUs, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use ...

data envelopment analysis (dea) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. it is based on solving linear programming problems. since 1978 when basic dea model was introduced many its modifications were formulated. among them are two or multi-stage models with serial or parallel structure often called net...

this paper deals with the problem of optimizing two-stage structure decision making units (dmus) where the activity and the performance of two-stage dmu in one period effect on its efficiency in the next period. to evaluate such systems the effect of activities in one period on ones in the next term must be considered. to do so, we propose a dynamic dea approach to measure the performance of su...

Problem statement: A variety of methods and algorithms for classification problems have been developed recently. But the main question is that how to select an appropriate and effective classification algorithm. This has always been an important and difficult issue. Approach: Since the classification algorithm selection task needs to examine more than one criterion such as accuracy and computat...

In this paper, a new three-stage virtual frontier SBM-DEA (Slacks-Based Measure of Efficiency in Data Envelopment Analysis) model is proposed to evaluate the sustainable efficiency construction industry. The relevant industry data 30 Chinese PARs (provincial administrative regions) from 2011 2016 are brought into calculate each region and verify rationality model. order solve problem that value...