Dynamic Multi-Objective Evolutionary Algorithm Based on Spectral Clustering Prediction

To address the challenge of rapidly tracking the new pareto optimal set (PS) after environmental changes in dynamic multi-objective optimization problems (DMOPs), this paper proposes a dynamic multi-objective evolutionary algorithm (DMOEA) based on spectral clustering prediction (SCP). The algorithm...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access Jg. 13; S. 176421 - 176433
Hauptverfasser:	Sheng, Zhao-Jun, Li, Erchao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Centroids Clustering Clustering algorithms Concavity Convexity Dynamic multi-objective optimization Dynamic tests evolutionary algorithm Evolutionary algorithms Evolutionary computation Genetic algorithms Heuristic algorithms Multiple objective analysis Optimization Pareto optimization Pareto optimum prediction Prediction algorithms Predictive models Recurrent neural networks Shape spectral clustering Transfer learning
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!