A generalized model for weight restrictions in data envelopment analysis

D L Tracy () and B Chen
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D L Tracy: The University of Tennessee at Martin
B Chen: Washington State University

Journal of the Operational Research Society, 2005, vol. 56, issue 4, 390-396

Abstract: Abstract Data envelopment analysis (DEA) is designed to maximize the efficiency of a given decision-making unit (DMU) relative to all other DMUs by the choice of a set of input and output weights. One strength of the original models is the absence of any need of a priori information about the process of transforming inputs into outputs. However, in the practical application of DEA models, this strength has also become a weakness. Incorporation of process knowledge is more a norm than an exception in practice, and typically involves placing constraints on the input and/or output weights. New DEA formulations have evolved to address this issue. However, existing formulations for weight restrictions may underestimate relative efficiency or even render a problem infeasible. A new model formulation is introduced to address this issue. This formulation represents a significant improvement over existing DEA models by providing a generalized, comprehensive treatment for weight restrictions.

Keywords: data envelopment analysis; parametric programming; fractional programming (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (7)

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DOI: 10.1057/palgrave.jors.2601823

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