Commenced in January 2007
Paper Count: 30855
Classifying and Predicting Efficiencies Using Interval DEA Grid Setting
Authors: Yiannis G. Smirlis
Abstract:The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1317188Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 360
 A. Charnes, W. W. Cooper and Rhodes E. “Measuring the efficiency of decision making units”, European Journal of Operational Research 1978; 2; 429-444.
 J. H. Dulá, F. J. López. “Data envelopment analysis (DEA) in massive data sets”, Kluwer Academic Publishers; 2002; ISBN 1-4020-0489-3.
 Y. Chen, A. I. Ali, “Output-Input ratio analysis and DEA frontier”, Journal of Operational Research, 2002, 142:476-479.
 Μ. Shaheen, “A Pre-Processor for the CCR Model in DEA”, in INFORMS National Conference, Miami, FL. (Nov. 6, 2001).
 Ali I. A, “Streamlined computation for data envelopment”, European Journal of Operational Research, Volume 64, Issue 1, 8 January 1993, Pages 61-67.
 E. W. Forgy (1965). "Cluster analysis of multivariate data: efficiency versus interpretability of classifications". Biometrics. 21: 768–769.
 W. W. Cooper, K. S. Park and G. Yu. “IDEA and AR-IDEA: Models for dealing with imprecise data in DEA”, Management Science. 1999; 45; 597-607.
 D. K. Despotis, Y. G. Smirlis, “Data Envelopment with Imprecise Data”, European Journal of Operational Research 2002; 140; 24-36.
 Wang. Y-M. R. Greatbanks, Jian-Bo Yang. 2005. “Interval efficiency assessment using data envelopment analysis”. Fuzzy Sets and Systems 153:347–370.