Abstract :
One of the most serious principles in production theory in economic
is the principle of "efficiency". Simply put, efficiency can be defined
as the demand that the desired goals (outputs) are achieved with the
minimum use of the available resources (inputs). In order to, distinguish
the relative efficiency of organizational units with multiple inputs
to produce multiple outputs, "Data Envelopment Analysis"
(DEA) method was introduced by Charnes, Cooper and Rhodes. In
fact, DEA is a linear mathematical programming which calculates the
efficiency of an organisation within a group relative to observed best
practice within that group. Unlike common statistical analysis which
are based on central tendencies, it is a methodology directed at the
frontier. Recently, DEA has become one of the most favorite fields in
operations research. The background was a motivation for us to in
this paper, via running the CCR model in "DEA-Solver Software",
present data envelopment analysis from simulation on the lattice QCD
with temporal extent Nτ=4,6, respectively. Astonishingly, results are
derived for both cases, indicating the fact that efficient data set belong
to the areas of high temperature (deconfinement phase). It is very interesting
to highlight that even an efficient data has not reported at
low temperature (confinement phase). Note that the data obtained at
the critical temperature is also efficient. As expected from practical
lattice QCD, the DEA-CCR model presented in this paper also confirms
the fact which the best data set arises from simulation in continuum
limit a→0. Indeed, by taking the limit of vanishing lattice
spacing, the efficiency of algorithms can be further.
Keywords :
Data Envelopment Analysis , CCR model , ranking model , Lattice QCD , continuum limit