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Autor Principal: Theodosopoulos, Ted
Formato: Preprint
Publicado: 2004
Subjects:
Acceso en liña:https://arxiv.org/abs/math/0406095
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author Theodosopoulos, Ted
author_facet Theodosopoulos, Ted
contents For a class of stochastic restart algorithms we address the effect of a nonzero level of randomization in maximizing the convergence rate for general energy landscapes. The resulting characterization of the optimal level of randomization is investigated computationally for random as well as parametric families of rugged energy landscapes.
format Preprint
id arxiv_https___arxiv_org_abs_math_0406095
institution arXiv
publishDate 2004
record_format arxiv
spellingShingle Some Remarks on the Optimal Level of Randomization in Global Optimization
Theodosopoulos, Ted
Optimization and Control
Numerical Analysis
Probability
65C40; 68W20; 90C26
For a class of stochastic restart algorithms we address the effect of a nonzero level of randomization in maximizing the convergence rate for general energy landscapes. The resulting characterization of the optimal level of randomization is investigated computationally for random as well as parametric families of rugged energy landscapes.
title Some Remarks on the Optimal Level of Randomization in Global Optimization
topic Optimization and Control
Numerical Analysis
Probability
65C40; 68W20; 90C26
url https://arxiv.org/abs/math/0406095