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...

Interval DEA frontiers are here used in situations where one input or output is subject to uncertainty in its measurement and is presented as an interval data. We built an efficient frontier without any assumption about the probability disttribution function of the imprecise variable. We take into account only the minimum and the maximum values of each imprecise variable. Two frontiers are cons...

An important outcome of assessing relative efficiencies within a group of decision making units (DMUs) in fuzzy data envelopment analysis is a set of virtual multipliers or weights accorded to each (input or output) factor taken into account. These sets of weights are, typically, different for each of the participating DMUs, and in some cases it may be considered unacceptable that the same fact...

In this study, both optimistic and pessimistic approaches of data envelopment analysis are applied to propose an equitable ranking method in fuzzy environments. To this end, we suppose that the sum of efficiency scores of all decision making units (DMUs) equals to unity. Using the worst-best and best-worst approaches, the minimum and maximum possible efficiency scores of each DMU are estimated ...

in this paper, we deal with fuzzy random variables for inputs andoutputs in data envelopment analysis (dea). these variables are considered as fuzzyrandom flat lr numbers with known distribution. the problem is to find a method forconverting the imprecise chance-constrained dea model into a crisp one. this can bedone by first, defuzzification of imprecise probability by constructing a suitablem...

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...