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Natural Computing

Erschienen in:

01.06.2016

On the model updating operators in univariate estimation of distribution algorithms

verfasst von: Andrey G. Bronevich, José Valente de Oliveira

Erschienen in: Natural Computing | Ausgabe 2/2016

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Abstract

The role of the selection operation—that stochastically discriminate between individuals based on their merit—on the updating of the probability model in univariate estimation of distribution algorithms is investigated. Necessary conditions for an operator to model selection in such a way that it can be used directly for updating the probability model are postulated. A family of such operators that generalize current model updating mechanisms is proposed. A thorough theoretical analysis of these operators is presented, including a study on operator equivalence. A comprehensive set of examples is provided aiming at illustrating key concepts, main results, and their relevance.

Vorheriger Artikel Global memory schemes for dynamic optimization

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Titel: On the model updating operators in univariate estimation of distribution algorithms
verfasst von: Andrey G. Bronevich
José Valente de Oliveira
Publikationsdatum: 01.06.2016
Verlag: Springer Netherlands
Erschienen in: Natural Computing / Ausgabe 2/2016
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI: https://doi.org/10.1007/s11047-015-9499-0

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