Interpolating Greedy and Reluctant Algorithms

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In a standard NP-complete optimization problem we introduce an interpolating algorithm between the quick decrease along the gradient (greedy dynamics) and a slow decrease close to the level curves (reluctant dynamics). We find that for a fixed elapsed computer time the best performance of the optimization is reached at a special value of the interpolation parameter, considerably improving the results of the pure cases greedy and reluctant.
9 pages. 3 figures

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Mathematical Physics, Disordered Systems and Neural Networks

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http://salesiana.dossiersoluciones.com/handle/123456789/57516

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/math-ph/0309063
 http://arxiv.org/abs/math-ph/0309063

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arXiv