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

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

2004-07-30

arxiv.org/abs/math-ph/0407078v1

Physics

Mathematical Physics

30 pages, 12 figures

Scientific paper

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.

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