EQUIVALENCES BETWEEN DATA ENVELOPMENT ANALYSIS AND THE THEORY OF REDUNDANCY IN LINEAR-SYSTEMS

This paper establishes how the non-parametric frontier estimation meth odology of Data Envelopment Analysis (DEA) and the classical problem o f detecting redundancy in a system of linear inequalities are connecte d. We present an analysis of the sets generated in two of DEA's models from where the empirical efficient production frontier is established from the point of view of polyhedral set theory. This yields convenie nt alternative characterizations of these sets which provide new insig hts about their properties. We use these insights to show how these po lyhedral sets connect DEA to redundancy in linear systems. This means that DEA can benefit from a rich and well-established collection of co mputational and theoretical results which apply directly from redundan cy in linear systems. (C) 1997 Published by Elsevier Science B.V.