Finding Minima in Complex Landscapes: Annealed, Greedy and Reluctant Algorithms
Mathematical Physics
2007-05-23 v1 math.MP
Numerical Analysis
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.
Cite
@article{arxiv.math-ph/0407078,
title = {Finding Minima in Complex Landscapes: Annealed, Greedy and Reluctant Algorithms},
author = {Pierluigi Contucci and Cristian Giardina' and Claudio Giberti and Cecilia Vernia},
journal= {arXiv preprint arXiv:math-ph/0407078},
year = {2007}
}
Comments
30 pages, 12 figures