In the original DEA/CCR (Data Envelopment Analysis/Charnes, Cooper and Rhodes) computation with n DMUs (Decision Making Units), we cannot make do with solving n LP (Linear Programming) problems even to judge only whether each DMU is DEA efficient or not in using ordinary LP solvers. This is because we must use two-phase optimization unless we have access to DEA software packages taking non-Archimedean infinitesimals into consideration. We must solve n Phase I LPs for all the n DMUs plus Phase II LPs to see whether DEA inefficient DMUs on the extended frontier are efficient. This paper shows that, through solving nearly n LPs, we can achieve two-phase optimization if we use the DEA exclusion model instead of the standard DEA model, etc. We should note a merit of the DEA exclusion model for reducing DEA computation load as well.
