inverse dea model with fuzzy data for output estimation

Inverse DEA Model with Fuzzy Data for Output Estimation

In this paper, we show that inverse Data Envelopment Analysis (DEA) models can be used to estimate output with fuzzy data for a Decision Making Unit (DMU) when some or all inputs are increased and deficiency level of the unit remains unchanged.

Multiple Fuzzy Regression Model for Fuzzy Input-Output Data

A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...

SBM Model with Fuzzy Input-output Levels in DEA

In this paper a model for fuzzy SBM of efficiency in DEA is presented based on a-cuts of the fuzzy number parameters to convert fuzzy linear programming problem to an interval programming problem. Then, by introducing a variable in each of the obtained intervals and applying suitable substitutions, a linear programming problem would be achieved. To demonstrate the concept, numerical examples ar...

Secondary Model Developed for Weight Selective in Evaluating the Efficiency of Cross-DEA with Fuzzy Data

Two-stage DEA with Fuzzy Data

Data envelopment analysis is a nonparametric technique checking efficiency of DMUs using math programming. In conventional DEA, it has been assumed that the status of each measure is clearly known as either input or output. Kao and Hwang (2008) developed a data envelopment analysis (DEA) approach for measuring efficiency of decision processes which can be divided into two stages. The first stag...

Inputs and Outputs Estimation in Inverse DEA

The present study addresses the following question: if among a group of decision making units, the decision maker is required to increase inputs and outputs to a particular unit in which the DMU, with respect to other DMUs, maintains or improves its current efficiencylevel, how much should the inputs and outputs of the DMU increase? This question is considered as a problem of inverse data envel...