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A Statistical Analysis of Performance in the 2021 CEC-GECCO-PESGM Competition on Evolutionary Computation in the Energy Domain

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dc.contributor.authorLezama, Fernando
dc.contributor.authorSoares, João
dc.contributor.authorCanizes, Bruno
dc.contributor.authorVale, Zita
dc.date.accessioned2023-03-14T09:32:30Z
dc.date.available2023-03-14T09:32:30Z
dc.date.issued2021
dc.description.abstractEvolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world applications with high complexity. However, due to the stochastic nature of the results obtained using EAs, the design of benchmarks and competitions where such approaches can be evaluated and compared is attracting attention in the field. In the energy domain, the “2021 CEC-GECCO-PESGM Competition on Evolutionary Computation in the Energy Domain: Smart Grid Applications” provides a platform to test and compare new EAs to solve complex problems in the field. However, the metric used to rank the algorithms is based solely on the mean fitness value (related to the objective function value only), which does not give statistical significance to the performance of the algorithms. Thus, this paper presents a statistical analysis using the Wilcoxon pair-wise comparison to study the performance of algorithms with statistical grounds. Results suggest that, for track 1 of the competition, only the winner approach (first place) is significantly different and superior to the other algorithms; in contrast, the second place is already statistically comparable to some other contestants. For track 2, all the winner approaches (first, second, and third) are statistically different from each other and the rest of the contestants. This type of analysis is important to have a deeper understanding of the stochastic performance of algorithms.pt_PT
dc.description.sponsorshipThis research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017(CENERGETIC),CEECIND/02814/2017, and UIDB/000760/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/SSCI50451.2021.9660117pt_PT
dc.identifier.isbn978-1-7281-9048-8
dc.identifier.urihttp://hdl.handle.net/10400.22/22464
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationPOCI01-0145-FEDER-028983pt_PT
dc.relationNot Available
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9660117pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEvolutionary computationpt_PT
dc.subjectMetaheuristicspt_PT
dc.subjectPower systemspt_PT
dc.subjectOptimizationpt_PT
dc.subjectSmart gridspt_PT
dc.titleA Statistical Analysis of Performance in the 2021 CEC-GECCO-PESGM Competition on Evolutionary Computation in the Energy Domainpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEEI-EEE%2F28983%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02814%2F2017%2FCP1417%2FCT0002/PT
oaire.citation.conferencePlaceOrlando, FL, USApt_PT
oaire.citation.endPage8pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2021 IEEE Symposium Series on Computational Intelligence (SSCI)pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStreamCEEC IND 2017
person.familyNameLezama
person.familyNameSoares
person.familyNameCanizes
person.familyNameVale
person.givenNameFernando
person.givenNameJoão
person.givenNameBruno
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-idA411-F561-E922
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-9808-5537
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridI-3492-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id35408699300
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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