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

2004/07/30 by Pierluigi Contucci, Cristian Giardinà, Contucci, Pierluigi +5
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Complex Systems and Time Series Analysis #Data Visualization and Analytics #FOS: Mathematics #FOS: Physical sciences #Mathematical Physics (math-ph) #Numerical Analysis (math.NA) #Theoretical and Computational Physics

paper · pdf · doi:10.48550/arxiv.math-ph/0407078

openalex publication_date 2004/07/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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