Empirical Study of Segment Particle Swarm Optimization and Particle Swarm Optimization Algorithms

In this paper, the performance of segment particle swarm optimization (Se-PSO) algorithm was compared with that of original particle swarm optimization (PSO) algorithm. Four different benchmark functions of Sphere, Rosenbrock, Rastrigin, and Griewank with asymmetric initial range settings (upper and...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of advanced computer science & applications 2019, Vol.10 (8)
Hauptverfasser: Azrag, Mohammed Adam Kunna, Asmawaty, Tuty
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this paper, the performance of segment particle swarm optimization (Se-PSO) algorithm was compared with that of original particle swarm optimization (PSO) algorithm. Four different benchmark functions of Sphere, Rosenbrock, Rastrigin, and Griewank with asymmetric initial range settings (upper and lower boundaries values) were selected as the test functions. The experimental results showed that, the Se-PSO algorithm achieved better results in terms of faster convergences in all the testing cases compared to the original PSO algorithm. However, the experimental results further showed the Se-PSO as a promising optimization algorithm method in some other different fields.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2019.0100862