Finding Minima in Complex Landscapes: Annealed, Greedy and Reluctant   Algorithms
  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. 
Pierluigi Contucci, Cristian Giardina', Claudio Giberti and Cecilia   Vernia