  We consider optimization problems for complex systems in which the cost
function has a multivalleyed landscape. We introduce a new class of dynamical
algorithms which, using a suitable annealing procedure coupled with a balanced
greedy-reluctant strategy drive the systems towards the deepest minimum of the
cost function. Results are presented for the Sherrington-Kirkpatrick model of
spin-glasses.
