data envelopment analysis (dea) is a mathematical programming-based approach for evaluates the relative efficiency of a set of dmus (decision making units). the relative efficiency of a dmu is the result of comparing the inputs and outputs of the dmu and those of other dmus in the pps (production possibility set). also, in data envelopment analysis various models have been developed in order to...

envelopment analysis (dea) is a very eective method to evaluate the relative eciency of decision-making units (dmus). dea models divided all dmus in two categories: ecient and inecientdmus, and don't able to discriminant between ecient dmus. on the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ...

Article Outline Glossary I. Definition of the Subject and Its Importance II. Introduction III. Mathematical modeling of imprecise data IV. Fuzzy random variables V. Statistical analysis of random fuzzy perceptions VI.1 Fuzzy estimators and fuzzy confidence intervals VI.2 Fuzzy statistical tests VII. Statistical analysis of random fuzzy variables VIII. Future directions Bibliography Glossary Fuz...

  In this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (IDEA) and mini-max reference point formulations. Through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. In addition, the gradient projection type...

The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...