A hyper-heuristic algorithm via proximal policy optimization for multi-objective truss problems

This paper proposes a hyper-heuristic evolutionary algorithm via proximal policy optimization, named HHEA-PPO, for solving multi-objective truss optimization problems. HHEA-PPO has a two-layer structure: a high-level strategy and low-level heuristics. The high-level strategy consists of proximal pol...

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Vydané v:	Expert systems with applications Ročník 256; s. 124929
Hlavní autori:	Yin, Shihong, Xiang, Zhengrong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 05.12.2024
Predmet:	Dynamic crowding distance Hyper-heuristic algorithm Multi-objective optimization Proximal policy optimization Truss optimization Hyper-heuristic algorithm Proximal policy optimization Multi-objective optimization Dynamic crowding distance Truss optimization
ISSN:	0957-4174
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