The data envelopment analytical hierarchy process (DEAHP) is a type of the analytical hierarchy process (AHP), which used the concept of data envelopment analysis (DEA) for generating LW from the judgment matrices and aggregating them to be final weight (FW) in AHP. In general, the judgment scales in AHP is built based on decision maker. It is unrealistic to expect that the decision maker has c...

During the last years, the concept of input congestion and technical ineff-ciency in data envelopment analysis (DEA), have been investigated by manyresearchers. The motivation of this paper is to present models which obtain thedecreased output value due to input congestion and technical ineciency. More-over, we extend the models to estimate input congestion, technical ineciencyand output reduct...

Qualitative input is encountered in many real decision-making domains. Often such domains include tradeoffs among multiple attributes, and estimates of parameters are often expressed with some degree of uncertainty. Grey related analysis has been proposed as a means to use interval fuzzy representation of data. When dealing with multiple criteria data, model parameters that can involve uncertai...

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...

Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency of decision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal pr...

In this study, Data Envelopment Analysis (DEA) models are improved by employing spherical fuzzy sets (SFSs), which is an extension of generalized sets. SFSs were recently introduced as a novel type set that allows decision-makers to express their level uncertainty directly. As result, provide more preferred domain for decision-makers. Fundamental Charnes-Cooper-Rhodes (CCR) model discussed on t...

The slack-based measure (SBM) DEA model is a non-radial used to calculate the relative efficiency, input, and output targets of different decision-making units (DMUs) based on their best peers or efficient frontier. conventional SBM crisp inputs outputs. But, it can be observed in real-life problems that sometimes available data linguistic forms such as “few”, “many”, “small”, missing data. tec...