  We consider the extremal pointset configuration problem of maximizing a
kernel-based energy subject to the geometric constraints that the points are
contained in a fixed set, the pairwise distances are bounded below, and that
every closed ball of fixed radius contains at least one point. We also
formulate an extremal density problem, whose solution provides an upper bound
for the pointset configuration problem in the limit as the number of points
tends to infinity. Existence of solutions to both problems is established and
the relationship between the parameters in the two problems is studied. Several
examples are studied in detail, including the density problem for the
$d$-dimensional ball and sphere, where the solution can be computed exactly
using rearrangement inequalities. We develop a computational method for the
density problem that is very similar to the Merriman-Bence-Osher (MBO)
diffusion-generated method. The method is proven to be increasing for all
non-stationary iterations and is applied to study more examples.
