History-Assisted Two-State Auxiliary Task Collaboration Approach for Dynamic Constrained Multiobjective Optimization

Dynamic constrained multiobjective optimization problems (DCMOPs) are widely encountered in real-world applications and have attracted increasing attention in the evolutionary computation community. Existing studies primarily focus on the population initialization, but disregard to improve the evolu...

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Veröffentlicht in:	IEEE transactions on evolutionary computation S. 1
Hauptverfasser:	Zhang, Dezheng, Yu, Kunjie, Liang, Jing, Qiao, Kangjia, Qu, Boyang, Chen, Ke, Yue, Caitong, Wang, Ling
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2024
Schlagworte:	Dynamic constrained multiobjective optimization Environment identify Evolutionary algorithm Evolutionary computation Heuristic algorithms Historical information Optimization Prediction algorithms Sociology Statistics Task analysis Two-state algorithm
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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