Spatial-Temporal Knowledge Transfer for Dynamic Constrained Multiobjective Optimization

Dynamic constrained multiobjective optimization problems (DCMOPs) are characterized by multiple conflicting optimization objectives and constraints that vary over time. The presence of both dynamism and constraints underscores the importance of preserving population diversity. This diversity is esse...

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Vydané v:	IEEE transactions on evolutionary computation Ročník 29; číslo 5; s. 1990 - 2003
Hlavní autori:	Wang, Zhenzhong, Xu, Dejun, Jiang, Min, Chen Tan, Kay
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.10.2025
Predmet:	Convergence Dynamic constrained multiobjective optimization evolutionary multitasking optimization Heuristic algorithms Knowledge transfer Optimization Pareto optimization Search problems Task analysis test suite
ISSN:	1089-778X, 1941-0026
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