Szczegóły publikacji

Opis bibliograficzny

Maximizing efficiency: a comparative study of SOMA algorithm variants and constraint handling methods for time delay system optimization / Roman Senkerik, Tomas Kadavy, Peter Janku, Michal Pluhacek, Hubert GUZOWSKI, Libor Pekar, Radek Matusu, Adam Viktorin, Maciej SMOŁKA, Aleksander BYRSKI, Zuzana Komínková Oplatková // W: GECCO'23 [Dokument elektroniczny] : Genetic and Evolutionary Computation Conference Companion : 15–19 July 2023, Lisbon, Portugal : proceedings. — Wersja do Windows. — Dane tekstowe. — USA : Association for Computing Machinery, cop. 2023. — e-ISBN: 979-8-4007-0120-7. — S. 1821–1829. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://dl.acm.org/doi/pdf/10.1145/3583133 [2023-08-07]. — Bibliogr. s. 1829, Abstr. — Publikacja dostępna online od: 2023-07-24. — M. Pluhacek – afiliacja: Tomas Bata University in Zlin, Czech Republic

Autorzy (11)

Słowa kluczowe

SOMAparametric optimizationtime delay systemswarm algorithms

Dane bibliometryczne

ID BaDAP148055
Data dodania do BaDAP2023-09-05
DOI10.1145/3583133.3596417
Rok publikacji2023
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaAssociation for Computing Machinery (ACM)
KonferencjaGenetic and Evolutionary Computations 2023

Abstract

This paper presents an experimental study that compares four adaptive variants of the self-organizing migrating algorithm (SOMA). Each variant uses three different constraint handling methods for the optimization of a time delay system model. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delayed systems to develop more effective and efficient control strategies and precise model identifications. The study includes a detailed description of the selected variants of the SOMA and the adaptive mechanisms used. A complex workflow of experiments is described, and the results and discussion are presented. The experimental results highlight the effectiveness of the SOMA variants with specific constraint handling methods for time delay system optimization. Overall, this study contributes to the understanding of the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of the SOMA variants and can help guide the selection of appropriate constraint handling methods and the adaptive mechanisms of metaheuristics.

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