This study proposes the Data Envelopment Analysis (DEA) ranking for resource allocation between Iran's Medical Universities based on a five years observation data (2004-2008). We compared the DEA ranking results with the traditional ranking approach applied by the Ministry of Health and Medical Education of Iran. Based on the DEA score the amount of budget is proposed for each university for th...

Anchor DMUs are a new class in the general classification of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). An anchor DMU in DEA is an extreme-efficient DMU that defines the transition from the efficient frontier to the free-disposability part of the boundary of the Production Possibility Set (PPS). In this paper, the anchor points of the PPS of the CCR model are investigated....

In this study, we propose a new Artificial Neural Networks (ANN) training approach that closes the gap between ANN and Data Envelopment Analysis (DEA), and has the advantage of giving similar results to DEA and being easier to compute. Our method is based on extreme point selection in a bandwidth while determining the training set, and it gives better results than the traditional ANN approach. ...

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

this paper investigates a procedure for identifying all efficient hyperplanes of production possibility set (pps). this procedure is based on a method which recommended by pekka j. korhonen[8]. he offered using of lexicographic parametric programming method for recognizing all efficient units in data envelopment analysis (dea). in this paper we can find efficient hyperplanes, via using the para...

One of the difficulties of Data Envelopment Analysis(DEA) is the problem of de_ciency discrimination among efficient Decision Making Units (DMUs) and hence, yielding large number of DMUs as efficient ones. The main purpose of this paper is to overcome this inability. One of the methods for ranking efficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this...

Data envelopment analysis (DEA) calculates the relative efficiency of homogenous decision-making units (DMUs) with multiple inputs and outputs. Classic DEA models usually suffer from several issues such as: discrimination power, variable weights of inputs/outputs, inaccurate efficiency estimation for small number of DMUs, incapability in working with zero and negative data, and not having exter...

Background and Objectives: Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate ...