Data Envelopment Analysis (DEA) is one of the best-known efficiency evaluation methods due to its advantages in selection of weights. Many research papers have extensively discussed the issue of weight restrictions, rather than those implied in the model itself. However, this often leads to a failure to represent the relations of certain weights, as well as underestimation of the efficiency of ...

sohrabi and nalchigar (2010) proposed a new data envelopment analysis (dea) model to identify the most efficient decision-making unit (dmu) in presence of imprecise data. in this paper, it is shown that the proposed model is not able to determine the most efficient dmu and is randomly introduced an efficient dmu. in addition, it is shown that this model determines the most efficient dmu in the ...

One of the weak points of DEA (Data Envelopment Analysis) models indicated in literature [1,2] is their sensitivity to variable measurement errors. The occurrence of data interference, which is the basis of the productivity analysis, may distort the classification of the units and may cause misjudgement of their effectiveness. In the article the results of simulation concerning the DEA models s...

The productivity change of a decision making unit (DMU) between two time periods can be evaluated by the Malmquist productivity index. In this study, we propose a method to compute the Malmquist productivity index in several time periods (from the first to the last periods) on interval data in data envelopment analysis (DEA). Then, the obtained Malmquist productivity index is compared with Malm...

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...

Although discriminating between all efficient decision making units (DMUs) with identical efficiency is a very important subject in data envelopment analysis (DEA), it may not be an easy task, particularly when the decision maker wants to select one and only one efficient DMU among all. There are some papers that have proposed methods for finding an efficient DMU as the most efficient one but h...

Cross-efficiency evaluation is an effective way of ranking decision making units (DMUs) in data envelopment analysis (DEA). Existing approaches for cross-efficiency evaluation are mainly focused on the calculation of cross-efficiency matrix, but pay little attention to the aggregation of the efficiencies in the cross-efficiency matrix. The most widely used approach is to aggregate the efficienc...

This paper introduces two virtual Decision Making Units (DMUs) called ideal point and anti-ideal point, Then calculates distances of each DMU to the ideal and anti-ideal point. The two distinctive distances are combined to form a comprehensive index called the relative closeness (RC) just like the TOPSIS approach. The RC index is used as an overall ranking for all the DMUs. Then, this method co...

Data envelopment analysis (DEA) is a mathematical programming method for calculatingefficiency of decision making units (DMU). In calculating the efficiency score of unitsthrough DEA we may come up with some efficient units. But the question is among theseefficient units which of them is better. As we know, it is possible to rank inefficient unitsthrough efficiency score; however, for ranking e...