A population-oriented hybrid search surrogate-assisted evolutionary algorithm for expensive constrained optimization multi-objective problems with small feasible regions

Multi-objective optimization problems with expensive objectives and constraints frequently arise in real industries, such problems are called expensive constrained multi-objective optimization problems(ECMOPs). Due to the expensive cost of actual fitness calculations, constructing suitable surrogate...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 99; S. 102161
Hauptverfasser:	Zhu, Cong, Yang, Yongkuan, Kong, Xiangsong, Li, Wenji
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2025
Schlagworte:	Data-driven Expensive constrained multi-objective optimization Multiple search strategies Small feasible region Surrogate models Expensive constrained multi-objective optimization Data-driven Surrogate models Small feasible region Multiple search strategies
ISSN:	2210-6502
Online-Zugang:	Volltext
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