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Nonrandom evolutionary algorithms

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dc.title Nonrandom evolutionary algorithms en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
dc.relation.ispartof MENDEL 2014
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-80-214-4984-8
dc.date.issued 2014
utb.relation.volume 2014-January
utb.relation.issue January
dc.citation.spage 123
dc.citation.epage 130
dc.event.title 20th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2014
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2014-06-25
dc.event.edate 2014-06-27
dc.type conferenceObject
dc.language.iso en
dc.publisher Brno University of Technology
dc.subject Deterministic chaos en
dc.subject Evolutionary algorithms en
dc.subject Periodic series en
dc.subject Pseudorandom numbers en
dc.description.abstract Inherent part of evolutionary algorithms that are based on Darwin theory of evolution and Mendel theory of genetic heritage, are random processes. In our as well as another researcher papers is successfully discussed possibility to replace pseudorandom number generators by deterministic chaos generator, generating chaos, and then by n periodical series based on deterministic chaos generators. Because all those previous experiments were successful or highly comparable with classical evolutionary algorithms powered by classical pseudorandom number generators, we extend our previous study on use classical mathematical periodical functions (very trivial one) and its use instead of pseudorandom number generators. Results presented here are numerical demonstration (partly of well know facts) rather than mathematical proofs. We open question whether evolutionary algorithms really need pseudorandom number generators or whether (and under what conditions) class of deterministic processes can be used without lowering the performance of evolutionary algorithms. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006226
utb.identifier.obdid 43871941
utb.identifier.scopus 2-s2.0-84938059546
utb.source d-scopus
dc.date.accessioned 2016-04-28T10:38:09Z
dc.date.available 2016-04-28T10:38:09Z
dc.description.sponsorship ESF, Czech Science Foundation; GACR, Czech Science Foundation
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pluháček, Michal
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