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A multi-objective approach to determine alternative targets in data envelopment analysis.

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Title: A multi-objective approach to determine alternative targets in data envelopment analysis.
Authors: Lins, M. P. Estellita1 estellit@iis.com.br, Angulo-Meza, L.1, da Silva, A. C. Moreira1
Source: Journal of the Operational Research Society. Oct2004, Vol. 55 Issue 10, p1090-1101. 12p.
Subjects: Data envelopment analysis, Multivariate analysis, Metric projections, A priori, Statistical decision making, Operations research
Abstract: The choice for radial projections of classic data envelopment analysis (DEA) models, resulting in a number of projections onto the Pareto-inefficient portion of the frontier, has been seen lately as a disadvantage in DEA. The search for a non-radial projection method resulted in developments such as preference structure models. These models consider a priori preference incorporation, using weights in the search for the most preferred efficient target, although presenting some implementation difficulties. In this paper, we propose a multi-objective approach that determines the bases for a posteriori preference incorporation, through individual projections of each variable (input or output) as an objective function, thus allowing one to obtain a target at every extreme-efficient point on the frontier. This multi-objective approach is shown to be equivalent to the preference structure models, yet presenting some advantages, such as the mapping of the possible weights, assigned to partial efficiencies of an observed unit, in order to reach a specific target. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:The choice for radial projections of classic data envelopment analysis (DEA) models, resulting in a number of projections onto the Pareto-inefficient portion of the frontier, has been seen lately as a disadvantage in DEA. The search for a non-radial projection method resulted in developments such as preference structure models. These models consider a priori preference incorporation, using weights in the search for the most preferred efficient target, although presenting some implementation difficulties. In this paper, we propose a multi-objective approach that determines the bases for a posteriori preference incorporation, through individual projections of each variable (input or output) as an objective function, thus allowing one to obtain a target at every extreme-efficient point on the frontier. This multi-objective approach is shown to be equivalent to the preference structure models, yet presenting some advantages, such as the mapping of the possible weights, assigned to partial efficiencies of an observed unit, in order to reach a specific target. [ABSTRACT FROM AUTHOR]
ISSN:01605682
DOI:10.1057/palgrave.jors.2601788