Why Tuning the Control Parameters of Metaheuristic Algorithms Is So Important for Fair Comparison?

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dc.contributor.authorKazikova, Anezka
dc.contributor.authorPluhacek, Michal
dc.contributor.authorSenkerik, Roman
dc.coverage.issue2cs
dc.coverage.volume26cs
dc.date.accessioned2021-08-10T11:28:31Z
dc.date.available2021-08-10T11:28:31Z
dc.date.issued2020-12-21cs
dc.description.abstractAlthough metaheuristic optimization has become a common practice, new bio-inspired algorithms often suffer from a priori ill reputation. One of the reasons is a common bad practice in metaheuristic proposals. It is essential to pay attention to the quality of conducted experiments, especially when comparing several algorithms among themselves. The comparisons should be fair and unbiased. This paper points to the importance of proper initial parameter configurations of the compared algorithms. We highlight the performance differences with several popular and recommended parameter configurations. Even though the parameter selection was mostly based on comprehensive tuning experiments, the algorithms' performance was surprisingly inconsistent, given various parameter settings. Based on the presented evidence, we conclude that paying attention to the metaheuristic algorithm's parameter tuning should be an integral part of the development and testing processes.en
dc.formattextcs
dc.format.extent9-16cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2020 vol. 26, č. 2, s. 9-16. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2020.2.009en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/200927
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/120cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectParameter tuningen
dc.subjectmetaheuristicsen
dc.subjectcomparisonen
dc.subjectswarm algorithmsen
dc.subjectconfigurationen
dc.subjectparticle swarm optimizationen
dc.titleWhy Tuning the Control Parameters of Metaheuristic Algorithms Is So Important for Fair Comparison?en
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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