Data envelopment analysis (DEA) is a non-parametric approach for measuring the efficiency of decision making units (DMUs) that use multiple inputs in order to produce multiple outputs. In most real applications, DMUs have a two-stage network process which can be used for management of organizations such as hospitals, insurance companies, banks, and etc. The data are crisp in the standard DEA mo...

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of peer operating units that employ multiple inputs to produce multiple outputs. Several DEA methods have been proposed for clustering operating units. However, to the best of our knowledge, the existing methods in the literature do not simultaneously consider the priority between the clusters (classes) and ...

Cost efficiency (CE) evaluates the ability to produce current outputs at minimal cost, given its input prices. In ordinary CE model, the input prices are assumed to be definite. In recent years, various attempts have been made to measuring CE when the input prices are as trapezoidal fuzzy numbers. The main contribution of this paper is to provide a new approach for generalizing the CE of decisi...

Data envelopment analysis (DEA) is a non-parametric technique to measure the efficiencies of a set of decision making units (DMUs) with common crisp inputs and outputs. In real-world problems, however, inputs and outputs typically have some levels of fuzziness. To analyze a DMU with fuzzy input/output data, previous studies provided the fuzzy DEA (FDEA) model and proposed an associated evaluati...

Mathematical programming is one of the areas to which fuq set theoq has been applied extensively. Primarily based on Bellman and Zadeh’s model of decision in fuzzy environments, models have been suggested which allow flexibility in constraints and nonlinear programming. Data envelopment analysis (DEA) is a method of evaluating relative efJiciencies for a group of similar units based on an efici...

in many real applications, the data of production processes can't be precisely measured.we develop some fuzzy versions of the classical dea models (in particular, the ccrmodel) by using some ranking methods based on the comparison of cuts. our approachescan be seen as an extension of the dea methodology. the provides users and practitionerswith models which represent some real life processes mo...

in many real applications, the data of production processes can't be precisely measured.we develop some fuzzy versions of the classical dea models (in particular, the ccrmodel) by using some ranking methods based on the comparison of cuts. our approachescan be seen as an extension of the dea methodology. the provides users and practitionerswith models which represent some real life process...

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision-making units (DMUs) on the basis of multiple inputs and outputs. Conventional DEA models assume that inputs and outputs are measured by exact values on a ratio scale. However, the observed values of the input and output data in real-world problems are often vague or random. Indeed, deci...

The purpose of this research paper is to develop a framework to understand the consumer’s preference affecting variables and consumer’s perception choice in telecommunication service providers in India. The present study use a hybrid approach to access the relative efficiency based on fuzzy AHP and DEA model. The fuzzy AHP is used to determine weights of the consumer’s preference as criteria an...