A Reinforcement Learning Hyper-Heuristic in Multi-Objective Optimization with Application to Structural Damage Identification

Multi-objective optimization allows satisfying multiple decision criteria concurrently, and generally yields multiple solutions. It has the potential to be applied to structural damage identification applications which are oftentimes under-determined. How to achieve high-quality solutions in terms o...

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Vydané v:	Structural and multidisciplinary optimization Ročník 66; číslo 1; s. 16
Hlavní autori:	Cao, Pei, Zhang, Yang, Tang, Jiong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	2230 Support Springer Nature (United States) 01.01.2023 Springer Berlin Heidelberg Springer Nature B.V
Predmet:	Advanced Optimization Enabling Digital Twin Technology Completeness Computational Mathematics and Numerical Analysis Damage detection Engineering Engineering Design Heuristic Interrogation Machine learning Mechanical Engineering Multiple objective analysis Optimization Research Paper Search algorithms Simulated annealing Structural damage Theoretical and Applied Mechanics Structural damage identification Multi-objective optimization Reinforcement learning Simulated annealing Hyper-heuristic
ISSN:	1615-147X, 1615-1488
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