Algorithms for the Frame of a Finitely Generated Unbounded Polyhedron
INFORMS Journal on Computing
A computational study of DEA with massive data sets
Computers and Operations Research
Efficient algorithm for additive and multiplicative models in data envelopment analysis
Operations Research Letters
An Algorithm for Data Envelopment Analysis
INFORMS Journal on Computing
Competing output-sensitive frame algorithms
Computational Geometry: Theory and Applications
An Algorithm for Data Envelopment Analysis
INFORMS Journal on Computing
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We collect, organize, analyze, implement, test, and compare a comprehensive list of ideas for preprocessors for entity classification in DEA. We limit our focus to procedures that do not involve solving LPs. The procedures are adaptations from previous work in DEA and in computational geometry. The result is five preprocessing methods three of which are new for DEA. Testing shows that preprocessors have the potential to classify a large number of DMUs economically making them an important computational tool especially in large scale applications. Scope and purpose: This is a comprehensive study of preprocessing in DEA. The purpose is to provide tools that will reduce the computational burden of DEA studies especially in large scale applications.