Chance-constrained DEA models with random fuzzy inputs and outputs

An ordinal ranking criterion for the subjective evaluation of alternatives and exchange reliability

“…Linguistic values similar to the ones used above are common in the literature on fuzzy decision making. See, among the most recent papers, [45,46,44]. In this paper, X d is just a set of values: the fact that this values can be numerical or linguistic does not play any role in the development of our results.…”

A bilateral exchange model: The paradox of quantifying the linguistic values of qualitative characteristics

“…The use of equally distributed (symmetric) TFNs is quite diffuse in the literature (see [36][37][38][39][40]). Our approach considers asymmetric TFNs and it is in this sense more general.…”

Chance-constrained data envelopment analysis modeling with random-rough data

“…Tavana et al [33] developed three imprecise DEA models in the presence of probability-possibility, probabilitynecessity and probability-credibility constraints where fuzziness and randomness simultaneously exist in an evaluation problem. Tavana et al [34] introduced random fuzzy variables in DEA when randomness and vagueness coexist in the same problem. The authors propose three DEA models for measuring the radial efficiency of DMUs when the input and output data are random fuzzy variables with Poisson, uniform and normal distributions.…”

“…In such cases, the concept of random-rough variable turns out to be a useful tool in dealing with these two types of uncertainty simultaneously. Recently Khanjani et al [12], Tavana et al ( [33,34], 2014) and Paryab et al [23] presented DEA models with two-fold uncertain data. Khanjani et al [12] proposed fuzzy rough DEA models based on the expected value and possibility approaches.…”