Enhancing Dynamic Constrained Multiobjective Optimization With Multicenters-Based Prediction

Dynamic constrained multiobjective optimization problems (DCMOPs) involve complex changes in objective functions and constraints over time. These changes challenge most existing algorithms to quickly cross infeasible regions and accurately track the changing Pareto optimal set (POS) and Pareto optim...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 29; H. 5; S. 1604 - 1618
Hauptverfasser:	Gong, Quan, Xia, Yizhang, Zou, Juan, Hou, Zhanglu, Liu, Yuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2025
Schlagworte:	Constraint handling Convergence Dynamic constrained multiobjective optimization Dynamic response Evolutionary computation Heuristic algorithms Linear programming multiobjective optimization problems (MOPs) Optical fibers Optimization Pareto optimization Prediction algorithms prediction strategy
ISSN:	1089-778X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!