Discrete Optimization of Statistical Sample Sizes in Simulation by Using
  the Hierarchical Bootstrap Method
  The Bootstrap method application in simulation supposes that value of random
variables are not generated during the simulation process but extracted from
available sample populations. In the case of Hierarchical Bootstrap the
function of interest is calculated recurrently using the calculation tree. In
the present paper we consider the optimization of sample sizes in each vertex
of the calculation tree. The dynamic programming method is used for this aim.
Proposed method allows to decrease a variance of system characteristic
estimators.
