Title: Optimality conditions and solution methodology for parameter selection in DEA

Authors: X. Zhang, N.C.P. Edirisinghe

Addresses: College of Business, Austin Peay State University, Clarksville, TN 37044, USA. ' College of Business Administration, University of Tennessee, Knoxville, TN 37996, USA

Abstract: This paper focuses on developing optimality conditions and a solution methodology for generalised Data Envelopment Analysis (GDEA). The GDEA framework determines input and output parameters in DEA models of internal managerial performance of Decision Making Units (DMUs) based on an optimisation criterion involving an external non-managerial reward function on DMU performance. The resulting problem is a difficult non-convex integer optimisation model. In this paper, first-order optimality conditions are first derived, and then, these are utilised within a hybrid scheme of gradient-based search and a metaheuristic such as simulated annealing for efficient solution. Data from a financial application are used to illustrate the methodology.

Keywords: data envelopment analysis; DEA; input selection; output selection; optimality conditions; gradient-based search; metaheuristics; simulated annealing; decision making; managerial performance; optimisation; parameter selection.

DOI: 10.1504/IJMOR.2011.040025

International Journal of Mathematics in Operational Research, 2011 Vol.3 No.3, pp.245 - 263

Published online: 12 Feb 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article