The random grid search (RGS) is a simple, but efficient, stochastic algorithm
to find optimal cuts that was developed in the context of the search for the
top quark at Fermilab in the mid-1990s. The algorithm, and associated code,
have been enhanced recently with the introduction of two new cut types, one of
which has been successfully used in searches for supersymmetry at the Large
Hadron Collider. The RGS optimization algorithm is described along with the
recent developments, which are illustrated with two examples from particle
physics. One explores the optimization of the selection of vector boson fusion
events in the four-lepton decay mode of the Higgs boson and the other optimizes
SUSY searches using boosted objects and the razor variables.Comment: 26 pages, 9 figure