Finding Minima in Complex Landscapes: Annealed, Greedy and Reluctant Algorithms

Abstract

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.

30 pages, 12 figures

References in corpus (3)

• Energy exponents and corrections to scaling in Ising spin glasses
• Comparing extremal and thermal Explorations of Energy Landscapes
• Optimization Strategies in Complex Systems