Network data envelopment analysis (NDEA), one of the most important branches recent DEA developments, has been developed for examining decision making units (DMUs) a system with complex and internal component divisions. In this study we apply maximin strategy to network at two levels. At individual DMU level, evaluate system’s performance by maximizing minimum divisions efficiencies, which is b...

Data Envelopment Analysis (DEA) is one of the best methods for measuring the efficiency and productivity of Decision Making Units (DMU). Evaluating the efficiency of DMUs which have two or several stages by using the conventional DEA models, is equal to consider them as black box. This method, omits the effect of intermediate measure on efficiency. Therefore, just the first network inputs and t...

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...

One of interesting subjects in Data Envelopment Analysis (DEA) is estimation congestion Decision Making Units (DMUs). Congestion evidenced when decreases (increases) some inputs result increases (decreases) outputs without worsening (improving) any other input/output. Most the existing methods for measuring DMUs utilize traditional definition and assume that change with same proportion. Therefo...

Data Envelopment Analysis (DEA) is a branch of management, concerned with evaluating the performances of homogeneous Decision Making Units (DMUs). The performances of DMUs are affected by the amount of sources that DMUs used. Usually increases in inputs cause increases in outputs. However, there are situations where increase in one or more inputs generate a reduction in one or more outputs. In ...

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...

     Data Envelopment Analysis (DEA) is an approach for evaluating performances of Decision Making Units (DMUs). The performances of DMUs are affected by the amount of sources that DMUs used. Usually increases in inputs cause increases in outputs. However, there are situations where increases in one or more inputs generate a reduction in one or more outputs. In such situations there is congesti...

In This paper a hybrid DEA method consisting of four phases for assigning the financial efficiency of commercial banks in India is used. This paper is based on panel data of banks for the period from 2011 to 2015. The DEA analysis based on hybrid method of DEA AND TOPSIS is used for ranking efficient Decision Making Units(DMUs) in Data Envelopment Analysis (DEA). However, since each of these me...

Data Envelopment Analysis (DEA) has been widely applied in measuring the efficiency of Decision-Making Units (DMUs). The conventional DEA three major drawbacks: a) it does not consider Decision Makers’ (DMs) preferences evaluation process, b) DMUs this model are flexible weighting criteria to reach maximum possible efficiency, and c) ignores uncertainty data. However, many real-world applicatio...