Maximizing efficiency: A comparative study of SOMA variants and constraint handling methods for time delay system optimization

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F23%3A63570998" target="_blank" >RIV/70883521:28140/23:63570998 - isvavai.cz</a>

Result on the web

<a href="https://dl.acm.org/doi/10.1145/3583133.3596417" target="_blank" >https://dl.acm.org/doi/10.1145/3583133.3596417</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3583133.3596417" target="_blank" >10.1145/3583133.3596417</a>

Result language

angličtina

Original language name

Maximizing efficiency: A comparative study of SOMA variants and constraint handling methods for time delay system optimization

Original language description

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. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GF21-45465L" target="_blank" >GF21-45465L: Metaheuristic-based parametric optimization of time-delay models and control systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

ISBN

979-840070120-7

ISSN

—

e-ISSN

—

Number of pages

9

Pages from-to

1821-1829

Publisher name

Association for Computing Machinery, Inc

Place of publication

New York

Event location

Lisbon

Event date

Jul 15, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001117972600295