Article ID: | iaor20115095 |
Volume: | 23 |
Issue: | 2 |
Start Page Number: | 284 |
End Page Number: | 296 |
Publication Date: | Mar 2011 |
Journal: | INFORMS Journal on Computing |
Authors: | Dul J H |
Keywords: | programming: linear |
The standard approach to process a data envelopment analysis (DEA) data set, and the one in widespread use, consists of solving as many linear programs (LPs) as there are entities. The dimensions of these LPs are determined by the size of the data sets, and they keep their dimensions as each decision‐making unit is scored. This approach can be computationally demanding, especially with large data sets. We present an algorithm for DEA based on a two‐phase procedure. The first phase identifies the extreme efficient entities, the