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Socio-cognitive optimization of time-delay control problems using agent-based metaheuristics

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dc.title Socio-cognitive optimization of time-delay control problems using agent-based metaheuristics en
dc.contributor.author Nabywaniec, Mateusz
dc.contributor.author Guzowski, Hubert
dc.contributor.author Urbańczyk, Aleksandra
dc.contributor.author Smołka, Maciej
dc.contributor.author Kisiel-Dorohinicki, Marek
dc.contributor.author Byrski, Aleksander
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pekař, Libor
dc.contributor.author Matušů, Radek
dc.contributor.author Gazdoš, František
dc.relation.ispartof 2022 IEEE 11th International Conference on Intelligent Systems, IS 2022
dc.identifier.isbn 978-1-6654-5656-2
dc.date.issued 2022
dc.event.title 11th IEEE International Conference on Intelligent Systems, IS 2022
dc.event.location Warsaw
utb.event.state-en Poland
utb.event.state-cs Polsko
dc.event.sdate 2022-10-12
dc.event.edate 2022-10-14
dc.type conferenceObject
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.identifier.doi 10.1109/IS57118.2022.10019693
dc.relation.uri https://ieeexplore.ieee.org/document/10019693
dc.relation.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10019693
dc.subject agent-based computing en
dc.subject hybrid metaheuristics en
dc.subject socio-cognitive computing en
dc.description.abstract Following the introduction of the socio-cognitive caste-based algorithms into the classic evolutionary metaheuristics, in this paper we focus on similar task regarding agent-based universal optimization methods. We tackle EMAS and DE algorithms and enrich them also with TOPSIS-inspired mechanism. Besides giving the details of the methods and the background, we present preliminary results after applying those techniques to solving the problem of optimization of time-delay system model. © 2022 IEEE. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1011417
utb.identifier.obdid 43884316
utb.identifier.scopus 2-s2.0-85147690525
utb.source d-scopus
dc.date.accessioned 2023-02-25T13:54:26Z
dc.date.available 2023-02-25T13:54:26Z
dc.description.sponsorship 978-1-5090-6008-5/17/$31.00; Grantová Agentura České Republiky, GA ČR: GF21-45465L; Narodowe Centrum Nauki, NCN: /35/O/ST6/00570, 2020/39/I/ST7/02285; Ministerstwo Edukacji i Nauki, MNiSW
dc.format.extent 7
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pekař, Libor
utb.contributor.internalauthor Matušů, Radek
utb.contributor.internalauthor Gazdoš, František
utb.fulltext.sponsorship The research presented in this paper was partially supported by: NCN project no: 2020/39/I/ST7/02285, NCN project: no: 2019/35/O/ST6/00570, Polish Ministry of Education and Science funds assigned to AGH University of Science and Technology. It was also supported by Czech Science Foundation (GACR) project no: GF21-45465L and resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation Agh University of Science and Technology, Institute of Computer Science, Krakow, Poland; Tomas Bata University in Zlín, Faculty of Applied Informatics, Czech Republic
utb.fulltext.projects 2020/39/I/ST7/02285
utb.fulltext.projects 2019/35/O/ST6/00570
utb.fulltext.projects GF21-45465L
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