  In this paper we describe NPSA, the first parallel nonparametric global
maximum likelihood optimization algorithm using simulated annealing (SA).
Unlike the nonparametric adaptive grid search method NPAG, which is not
guaranteed to find a global optimum solution, and may suffer from the curse of
dimensionality, NPSA is a global optimizer and it is free from these grid
related issues. We illustrate NPSA by a number of examples including a
pharmacokinetics (PK) model for Voriconazole and show that NPSA may be taken as
an upgrade to the current grid search based nonparametric methods.
