Finding minima in complex landscapes : annealed, greedy and reluctant algorithms

P. Contucci; C. Giardinà; C. Giberti; C. Vernia

doi:10.1142/S0218202505000765

Finding minima in complex landscapes : annealed, greedy and reluctant algorithms

P. Contucci, C. Giardinà, C. Giberti, C. Vernia

Research output: Contribution to journal › Article › Academic › peer-review

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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.

Original language	English
Pages (from-to)	1349-1370
Journal	Mathematical Models & Methods in Applied Sciences
Volume	15
Issue number	9
DOIs	https://doi.org/10.1142/S0218202505000765
Publication status	Published - 2005

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title = "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.",

author = "P. Contucci and C. Giardin{\`a} and C. Giberti and C. Vernia",

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T1 - Finding minima in complex landscapes : annealed, greedy and reluctant algorithms

AU - Contucci, P.

AU - Giardinà, C.

AU - Giberti, C.

AU - Vernia, C.

PY - 2005

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N2 - 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.

AB - 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.

U2 - 10.1142/S0218202505000765

DO - 10.1142/S0218202505000765

M3 - Article

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VL - 15

SP - 1349

EP - 1370

JO - Mathematical Models & Methods in Applied Sciences

JF - Mathematical Models & Methods in Applied Sciences

IS - 9

ER -

Finding minima in complex landscapes : annealed, greedy and reluctant algorithms

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