Measuring a Dynamic Efficiency Based on MONLP Model under DEA Control

Abstract

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent paper by afarian-Moghaddam and Ghoseiri [Jafarian-Moghaddam, A.R., Ghoseiri k., 2011. Fuzzy dynamic multi-objective Data Envelopment Analysis model. <em>Expert Systems with Applications</em>, 38 (1), 850-855.] they contribute to an interesting topic by presenting a ‎‎fuzzy dynamic multi-objective DEA model to evaluate DMUs in which ‎‎data are changing with time‎. However, this paper finds that their approach has some problems in the proposed models. In this paper, we first stress the present shortcomings in their modeling and then we propose a new DEA method for improving fuzzy dynamic multi-objective DEA model. The proposed model is a ‎‎multi-objective non-linear programming (MONLP) problem and there are ‎‎several methods for solving it; We use the goal programming (GP) method‎. ‎The proposed model calculates the efficiency scores of DMUs by‎‎ solving only one linear programming problem‎. ‎Finally‎, ‎we present an ‎‎example with ten DMUs at three times to illustrate the applicability the proposed model.