Detail publikace
An Investigation of Structural Bias in Particle Swarm Optimization
IBEHEJ, D. KŮDELA, J.
Anglický název
An Investigation of Structural Bias in Particle Swarm Optimization
Typ
Stať ve sborníku v databázi WoS či Scopus
Jazyk
en
Originální abstrakt
Many complex optimization problems, for which standard methods do not provide good-enough solutions, require the utilization of efficient metaheuristics. However, it has been found that several metaheuristics suffer from different types of structural biases, that may undermine their performance. In this paper, we investigate one of the most used evolutionary computation methods, the Particle Swarm Optimization algorithm. We utilize a recently developed modular framework for the construction of 123,900 parameterizations of PSO and investigate the effect of the different parameter choices on the identified types of structural bias. We also analyze and discuss the impact of the different types of structural bias found in these parameterizations on their performance on functions from a standard test set.
Klíčová slova anglicky
Bias; Evolutionary computation; Metaheuristics; Particle Swarm Optimization
Vydáno
2025-04-17
Nakladatel
Springer Science and Business Media Deutschland GmbH
ISBN
9783031900648
Kniha
Lecture Notes in Computer Science
Strany od–do
129–144
Počet stran
16
BIBTEX
@inproceedings{BUT200145,
author="David {Ibehej} and Jakub {Kůdela}",
title="An Investigation of Structural Bias in Particle Swarm Optimization",
booktitle="Lecture Notes in Computer Science",
year="2025",
journal="Lecture Notes in Computer Science",
pages="129--144",
publisher="Springer Science and Business Media Deutschland GmbH",
doi="10.1007/978-3-031-90065-5\{_}8",
isbn="9783031900648"
}