DEA2H2: differential evolution architecture based adaptive hyper-heuristic algorithm for continuous optimization

This paper proposes a novel differential evolution (DE) architecture based hyper-heuristic algorithm (DEA 2 H 2 ) for solving continuous optimization tasks. A representative hyper-heuristic algorithm consists of two main components: low-level and high-level components. In the low-level component, DE...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Cluster computing Jg. 27; H. 9; S. 12239 - 12266
Hauptverfasser:	Zhong, Rui, Yu, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2024 Springer Nature B.V
Schlagworte:	Ablation Adaptation Adaptive algorithms Computer Communication Networks Computer Science Deep learning Distance learning Effectiveness Evolutionary algorithms Evolutionary computation Genetic algorithms Heuristic Heuristic methods Mutation Operating Systems Operators (mathematics) Optimization Optimization techniques Performance evaluation Processor Architectures Searching Source code Statistical analysis Success Hyper-heuristic (HH) Success history knowledge Continuous optimization Differential evolution (DE)
ISSN:	1386-7857, 1573-7543
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!