Exploring the frequency of boundary control methods activation in metaheuristic algorithms

Kadavý, Tomáš; Pluháček, Michal; Viktorin, Adam; Šenkeřík, Roman

dc.title	Exploring the frequency of boundary control methods activation in metaheuristic algorithms	en
dc.contributor.author	Kadavý, Tomáš
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Viktorin, Adam
dc.contributor.author	Šenkeřík, Roman
dc.relation.ispartof	GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion
dc.identifier.isbn	979-840070120-7
dc.date.issued	2023
dc.citation.spage	2330
dc.citation.epage	2336
dc.event.title	2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion
dc.event.location	Lisbon
utb.event.state-en	Portugal
utb.event.state-cs	Portugalsko
dc.event.sdate	2023-07-15
dc.event.edate	2023-07-19
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Association for Computing Machinery, Inc
dc.identifier.doi	10.1145/3583133.3596418
dc.relation.uri	https://dl.acm.org/doi/10.1145/3583133.3596418
dc.relation.uri	https://dl.acm.org/doi/pdf/10.1145/3583133.3596418
dc.subject	evolutionary computation	en
dc.subject	computational intelligence	en
dc.subject	performance evaluation	en
dc.subject	benchmark testing	en
dc.subject	boundary control method	en
dc.description.abstract	Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem’s dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1011664
utb.identifier.obdid	43884591
utb.identifier.scopus	2-s2.0-85169071850
utb.identifier.wok	001117972600363
utb.source	d-scopus
dc.date.accessioned	2023-12-05T11:36:26Z
dc.date.available	2023-12-05T11:36:26Z
dc.description.sponsorship	Faculty of Applied Informatics, Tomas Bata University in Zlin; Tomas Bata University in Zlin, TBU, (IGA/CebiaTech/2023/004)
dc.description.sponsorship	Internal Grant Agency of the Tomas Bata University in Zlin [IGA/CebiaTech/2023/004]
utb.contributor.internalauthor	Kadavý, Tomáš
utb.contributor.internalauthor	Pluháček, Michal
utb.contributor.internalauthor	Viktorin, Adam
utb.contributor.internalauthor	Šenkeřík, Roman
utb.fulltext.sponsorship	The research presented in this paper was supported by: the Internal Grant Agency of the Tomas Bata University in Zlin, under project number IGA/CebiaTech/2023/004, and resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.wos.affiliation	[Kadavy, Tomas; Pluhacek, Michal; Viktorin, Adam; Senkerik, Roman] Tomas Bata Univ Zlin, Zlin, Czech Republic
utb.scopus.affiliation	Tomas Bata University in Zlin, Zlin, Czech Republic
utb.fulltext.projects	IGA/CebiaTech/2023/004