A dimensional decomposition approach to identifying efficient units in large-scale DEA models

Authors:
Pekka J. Korhonen;Pyry-Antti Siitari
Affiliations:
Department of Business Technology, Helsinki School of Economics, P.O. Box 1210, 00101 Helsinki, Finland;Department of Business Technology, Helsinki School of Economics, P.O. Box 1210, 00101 Helsinki, Finland
Venue:
Computers and Operations Research
Year:
2009

Citing 7
Cited 1

A procedure for ranking efficient units in data envelopment analysis

Management Science
Profit, directional distance functions, and Nerlovian efficiency

Journal of Optimization Theory and Applications
A Value Efficiency Approach to Incorporating Preference Information in Data Envelopment Analysis

Management Science
Data Envelopment Analysis: Theory, Methodology and Application

Data Envelopment Analysis: Theory, Methodology and Application
An Algorithm for Identifying the Frame of a Pointed Finite Conical Hull

INFORMS Journal on Computing
Data envelopment analysis (DEA) in massive data sets

Handbook of massive data sets
Using lexicographic parametric programming for identifying efficient units in DEA

Computers and Operations Research

Competing output-sensitive frame algorithms

Computational Geometry: Theory and Applications

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, we propose the use of a dimensional decomposition procedure together with lexicographic parametric programming to reduce computational burden when identifying the efficient decision making units in data envelopment analysis (DEA). The use of lexicographic parametric programming makes it possible to develop an efficient algorithm for the problems with few inputs and outputs. Based on this we propose the procedure which first partitions the original problem dimensionally into sub-problems and then identifies the efficient units of the sub-problems. Since those units are a subset of the weakly efficient solutions of the original problem, they are used as an initial approximation for the efficient units of the original problem. The efficiency of the approach is illustrated by numerical results.