TBU Publications
Repository of TBU Publications

On convergence of evolutionary algorithms powered by non-random generators

DSpace Repository

Show simple item record


dc.title On convergence of evolutionary algorithms powered by non-random generators en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Davendra, Donald David
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
dc.contributor.author Komínková Oplatková, Zuzana
dc.relation.ispartof Artificial Intelligence and Soft Computing 2014, Part I
dc.identifier.issn 0302-9743 OCLC, Ulrich, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-319-07172-5
dc.identifier.isbn 978-3-319-07173-2
dc.date.issued 2014
utb.relation.volume 8467
dc.citation.spage 492
dc.citation.epage 502
dc.event.title 13th International Conference on Artificial Intelligence and Soft Computing (ICAISC)
dc.event.location Zakopane
utb.event.state-en Poland
utb.event.state-cs Polsko
dc.event.sdate 2014-06-01
dc.event.edate 2014-06-05
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer-Verlag Berlin
dc.identifier.doi 10.1007/978-3-319-07173-2_42
dc.relation.uri http://link.springer.com/chapter/10.1007/978-3-319-07173-2_42
dc.subject evolutionary algorithms en
dc.subject non-random generators en
dc.subject pseudorandom generators en
dc.subject deterministic chaos 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 that are used in every evolutionary algorithm like genetic algorithms etc. In this paper we present experiments (based on our previous) of selected evolutionary algorithms and test functions demonstrating impact of non-random generators on performance of the evolutionary algorithms. In our experiments we used differential evolution and SOMA algorithms with functions Griewangk and Rastrigin. We use n periodical deterministic processes (based on deterministic chaos principles) instead of pseudorandom number generators and compare performance of evolutionary algorithms powered by those processes and by pseudorandom number generators. Results presented here has to be understand like numerical demonstration rather than mathematical proofs. Our results (reported sooner and here) suggest hypothesis that certain class of deterministic processes can be used instead of random number generators without lowering the performance of evolutionary algorithms. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1004158
utb.identifier.obdid 43871966
utb.identifier.scopus 2-s2.0-84902578416
utb.identifier.wok 000341246000042
utb.source d-wok
dc.date.accessioned 2015-02-17T15:13:02Z
dc.date.available 2015-02-17T15:13:02Z
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Komínková Oplatková, Zuzana
Find Full text

Files in this item

Show simple item record