Stationary probability density of stochastic search processes in global optimization

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dc.creatorBerrones, Arturo
dc.date2007-10-18
dc.date.accessioned2026-07-07T08:56:59Z
dc.date.available2026-07-07T08:56:59Z
dc.descriptionA method for the construction of approximate analytical expressions for the stationary marginal densities of general stochastic search processes is proposed. By the marginal densities, regions of the search space that with high probability contain the global optima can be readily defined. The density estimation procedure involves a controlled number of linear operations, with a computational cost per iteration that grows linearly with problem size.
dc.identifierhttps://arxiv.org/abs/0710.3561
dc.identifierhttp://arxiv.org/abs/0710.3561
dc.identifierJ. Stat. Mech. (2008) P01013
dc.identifierdoi:10.1088/1742-5468/2008/01/P01013
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/146809
dc.subjectArtificial Intelligence
dc.subjectStatistical Mechanics
dc.subjectNeural and Evolutionary Computing
dc.titleStationary probability density of stochastic search processes in global optimization
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