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Computer Science > Neural and Evolutionary Computing

arXiv:2210.12872 (cs)
[Submitted on 23 Oct 2022]

Title:Socio-cognitive Optimization of Time-delay Control Problems using Evolutionary Metaheuristics

Authors:Piotr Kipinski, Hubert Guzowski, Aleksandra Urbanczyk, Maciej Smolka, Marek Kisiel-Dorohinicki, Aleksander Byrski, Zuzana Kominkova Oplatkova, Roman Senkerik, Libor Pekar, Radek Matusu, Frantisek Gazdos
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Abstract:Metaheuristics are universal optimization algorithms which should be used for solving difficult problems, unsolvable by classic approaches. In this paper we aim at constructing novel socio-cognitive metaheuristic based on castes, and apply several versions of this algorithm to optimization of time-delay system model. Besides giving the background and the details of the proposed algorithms we apply them to optimization of selected variants of the problem and discuss the results.
Comments: In proceedings of the Intelligent Systems IS2022 Conference, October 12-14, 2022, Warsaw, Poland
Subjects: Neural and Evolutionary Computing (cs.NE); Artificial Intelligence (cs.AI)
ACM classes: I.2.11; I.2.8
Cite as: arXiv:2210.12872 [cs.NE]
  (or arXiv:2210.12872v1 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2210.12872

Submission history

From: Aleksander Byrski [view email]
[v1] Sun, 23 Oct 2022 22:21:10 UTC (1,014 KB)
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