data envelopment analysis (dea) is a method for measuring the relative efficiencies of a set of decision-making units (dmus) that use multiple inputs to produce multiple outputs. in this paper, we study the measurement of dmu performances in dea in situations where input and/or output values are given as imprecise data. by imprecise data we mean situations where we only know that the actual val...

in some data envelopment analysis (dea) applications, some inputs of dmus have negative values with positive cost. this paper generalizes the global cost malmquist productivity index to compare the productivity of dierent dmus with negative inputs in any two periods of times under variable returns to scale (vrs) technology, and then the generalized index is decomposed to several components. th...

background: assessment of hospitals’ performance in achieving its goals is a basic necessity. measuring the efficiency of hospitals in order to boost resource productivity in healthcare organizations is extremely important. the aim of this study was to measure technical efficiency and determining status of resource allocation in some university hospitals, in tehran, iran.   methods : this study...

one of the important issues in data envelopment analysis (dea) is sensitivity analysis. heretofore the existent studies have considered the data modification of inputs and outputs in one or multiple dmus. in this paper the number of dmus is increased and a stability region is obtained in  by applying defining hyperplanes in which if the added dmu (only one dmu) is in this region then all of the...

There are situations that Decision Making Units (DMU’s) have uncertain information and their inputs and outputs cannot alter redially. To this end, this paper combines the rough set theorem (RST) and Data Envelopment Analysis (DEA) and proposes a non-redial Rough-DEA (RDEA) model so called additive rough-DEA model and illustrates the proposed model by a numerical example.