An offline-online learning framework combining meta-learning and reinforcement learning for evolutionary multi-objective optimization

•An offline-online learning framework combining meta-learning and reinforcement learning (O2-MRL) is first proposed for evolutionary multi-objective optimization. O2-MRL can adaptively select and schedule the most appropriate MOEAs for diverse MOPs, thereby fully leveraging the complementary strengt...

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Vydané v:	Swarm and evolutionary computation Ročník 97; s. 102037
Hlavní autori:	Li, Shuxiang, Pang, Yongsheng, Huang, Zhaorong, Chu, Xianghua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.08.2025
Predmet:	Meta-learning Multi-objective optimization Offline algorithm selection Online algorithm selection Reinforcement learning Multi-objective optimization Online algorithm selection Offline algorithm selection Meta-learning Reinforcement learning
ISSN:	2210-6502
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