  The accuracy of Green Function Monte Carlo (GFMC) simulations can be greatly
improved by a clever choice of the approximate ground state wave function that
controls configuration sampling. This trial wave function typically depends on
many free parameters whose fixing is a non trivial task. Here, we discuss a
general purpose adaptive algorithm for their non-linear optimization. As a non
trivial application we test the method on the two dimensional Wess-Zumino
model, a relativistically invariant supersymmetric field theory with
interacting bosonic and fermionic degrees of freedom.
