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...

the performance of a decision making unit (dmu) can be evaluated in either across-sectional or a time-series manner, and data envelopment analysis (dea) is a useful method for both types of evaluation. the malmquist productivity index (mpi) evaluates the change in efficiency of a dmu between two time periods. it is defined as the product of the catch-up and frontier-shift terms. in this paper, ...

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...

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 ...

Technique of Data Envelopment Analysis (DEA) involves methods conducted for desirable objective management of Decision Making Unit (DMU) that is same increasing of efficiency level. Data envelopment analysis furthermore determines the efficiency level, provides situation, removes inefficiency with evaluated benchmarking information. In this paper the use of the improvement Least-Distance measur...

in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.

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 ...

   The performance of a decision making unit (DMU) can be evaluated in either across-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. The Malmquist productivity index (MPI) evaluates the change in efficiency of a DMU between two time periods. It is defined as the product of the Catch-up and Frontier-shift terms. In this pape...

Data envelopment analysis is a method for evaluating the relative efficiency of a collection of decision making units. The DEA classic models calculate each unit’s efficiency in the best condition, meaning that finds a weight that the DMU is at its maximum efficiency. In this paper, utilizing the directional distance function model in the presence of undesirable outputs, the efficiency of each ...