for efficiency evaluation of some of the decision making units that have uncertain information, rough data envelopment analysis technique is used, which is derived from rough set theorem and data envelopment analysis (dea). in some situations rough data alter nonradially. to this end, this paper proposes additive rough–dea model and illustrates the proposed model by a numerical example.

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 which may be less than or equal to one is obtained. Given the possible large number of efficiency units for evaluating units, we use various methods of ranking. span style="font-family: Cambria Math;font-size:8pt...

Data Envelopment Analysis (DEA) is a technique that uses all collected observations to measure performance. This method presents no data about how to operate on DMU. The present research attempted to study a unit with all its subunits, if the unit is efficient, it means that all its subunits are efficient too and if it is an inefficient, it shows clearly that which one of the subunits makes ine...

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...

Data envelopment analysis (DEA) is one of the most efficient tools for efficiency measurement which can be employed as a benchmarking method with multiple inputs and outputs. However, DEA does not provide any suggestions for improving efficient units, nor does it provide any benchmark or reference point for these efficient units. Impracticability of these benchmarks under environmental conditio...

In assessing the relative efficiency of decision-maker units by classical Data Envelopment Analysis (DEA) models, the status of the data is determined from the input or output points of views. In real issues, there are some data whose statuses are debatable. Some decision making units consider them as input to achieve higher efficiency while some other decision making units consider them ...

The ways of placing decision making units (DMUs) in certain clusters are found as a subject in statistics, these ways usually are heuristic. The proposed clustering approach in this article considers preferences of DMUs. This study applies Data Envelopment Analysis (DEA) DMUs are clustered by solving multi-objective linear problem (MOLP) and by considering preferences of each DMU at production ...