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Hybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimization

2019-07Conference object Open access
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dc.contributor.authorLezama, Fernando
dc.contributor.authorSoares, João
dc.contributor.authorFaia, R.
dc.contributor.authorVale, Zita
dc.date.accessioned2021-06-17T10:53:30Z
dc.date.available2021-06-17T10:53:30Z
dc.date.issued2019-07
dc.description.abstractIn this paper, a hybrid-adaptive differential evolution with a decay function (HyDE-DF)1 is proposed for numerical function optimization. The proposed HyDE-DF is applied to the 100-Digit Challenge in a set of 10 benchmark functions. Results show that HyDE-DF can achieve a 93/100 score, proving its effectiveness for numerical optimization.pt_PT
dc.description.sponsorshipThis research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1145/3319619.3326747pt_PT
dc.identifier.isbn978-1-4503-6748-6
dc.identifier.urihttp://hdl.handle.net/10400.22/18060
dc.language.isoengpt_PT
dc.publisherACMpt_PT
dc.relationPOCI-01-0145-FEDER-028983pt_PT
dc.relation.publisherversionhttps://dl.acm.org/doi/10.1145/3319619.3326747pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectComputing methodologiespt_PT
dc.subjectApplied computingpt_PT
dc.subjectSearch methodologiespt_PT
dc.subjectEngineeringpt_PT
dc.subjectEvolutionary computationpt_PT
dc.subjectDifferential evolutionpt_PT
dc.subjectnumerical optimizationpt_PT
dc.titleHybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimizationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEEI-EEE%2F28983%2F2017/PT
oaire.citation.conferencePlacePrague, Czech Republicpt_PT
oaire.citation.endPage8pt_PT
oaire.citation.startPage7pt_PT
oaire.citation.titleGECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companionpt_PT
oaire.fundingStream9471 - RIDTI
person.familyNameLezama
person.familyNameSoares
person.familyNameFaia
person.familyNameVale
person.givenNameFernando
person.givenNameJoão
person.givenNameRicardo Francisco Marcos
person.givenNameZita
person.identifier1043580
person.identifier78FtZwIAAAAJ
person.identifier632184
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id9B12-19F6-D6C7
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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