Authors: Saber Saati, Adel Hatami-Marbini, Madjid Tavana
Addresses: Department of Mathematics, Tehran-North Branch, Islamic Azad University, P.O. Box 19585-936, Tehran, Iran. ' Louvain School of Management, Center of Operations Research and Econometrics (CORE), Universite Catholique de Louvain, 34 Voie du Roman Pays, Louvain-la-Neuve B-1348, Belgium. ' Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA 19141, USA
Abstract: Data envelopment analysis (DEA) is a powerful mathematical method that utilises linear programming (LP) to determine the relative efficiencies of a set of functionally similar decision-making units (DMUs). Evaluating the efficiency of DMUs continues to be a difficult problem to solve, especially when the multiplicity of inputs and outputs associated with these units is considered. Problems related to computational complexities arise when there are a relatively large number of redundant variables and constraints in the problem. In this paper, we propose a three-step algorithm to reduce the computational complexities and costs in the multiplier DEA problems. In the first step, we identify some of the inefficient DMUs through input–output comparisons. In the second step, we specify the efficient DMUs by solving a LP model. In the third step, we use the results derived from the second step and another LP model to obtain the efficiency of the inefficient DMUs. We also present a numerical example to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.
Keywords: DEA; data envelopment analysis; duo linear programming; DMU; decision making units; multipliers; efficiency determination.
International Journal of Productivity and Quality Management, 2011 Vol.7 No.1, pp.90 - 103
Published online: 26 Dec 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article