  We present a computer-assisted approach to locating approximate coarse
optimal switching policies between stationary states of chemically reacting
systems described by microscopic/stochastic evolution rules. The ``coarse
time-stepper" constitutes a bridge between the underlying kinetic Monte Carlo
simulation and traditional, continuum numerical optimization techniques
formulated in discrete time. The approach is illustrated through two simple
catalytic surface reaction models, implemented through kinetic Monte Carlo: NO
reduction on Pt, and CO oxidation on Pt. The objective sought in both cases is
to switch between two coexisting stable stationary states by minimal
manipulation of a macroscopic system parameter.
