The existing data envelopment analysis (DEA) models for measuring the relative efficiencies of a set of decision making units (DMUs) using various inputs to produce various outputs are limited to crisp data. The notion of fuzziness has been introduced to deal with imprecise data. Fuzzy DEA models are made more powerful for applications. This paper develops the measure of efficiencies in input o...

The ability of determining all defining hyperplanes of DEA production possibility set (efficient frontier) prior to the DEA computations is of extreme importance. Specially, access to efficient frontier permits a complete analysis (e.g. calculation of efficiency scores, returns to scale, sensitivity analysis and so on) in second phase for the corresponding model. This paper presents a linear sy...

The relationship is studied between possibility and necessity measures defined on arbitrary spaces, the theory of imprecise probabilities, and elementary random set theory. It is shown how special random sets can be used to generate normal possibility and necessity measures, as well as their natural extensions. This leads to interesting alternative formulas for the calculation of these natural ...

We study the relationship between possibility and necessity measures defined on arbitrary spaces, the theory of imprecise probabilities, and elementary random set theory. We show how special random sets can be used to generate normal possibility and necessity measures, as well as their natural extensions. This leads to interesting alternative formulas for the calculation of these natural extens...

The paper proposes a diagnostic method using possibility theory. According to possibility theory, fuzzy set A on a set of possible causes U, B on possible symptoms V, and a fuzzy relation R on U ́V could be understood as possibility distributions pU(ui), pV(vj) and a conditional possibility distribution pV1⁄2U(vj1⁄2ui), respectively. In this paper, we define diagnosis as a problem to obtain poss...

In this paper, we consider several types of in­ formation and methods of combination asso­ ciated with incomplete probabilistic systems. \Ve discriminate between 'a priori' and evi­ dential information. The former one is a de­ scription of the whole population, the latest is a restriction based on observations for a particular case. Then, we proposse different combination methods for each one o...

  We suggest a method for finding the non-dominated points of the production possibility set (PPS) with variable returns to scale (VRS) technology in data envelopment analysis (DEA). We present a multiobjective linear programming (MOLP) problem whose feasible region is the same as the PPS under variable returns to scale for generating non-dominated points. We demonstrate that Pareto solutions o...