pBO-2GP-3B: a batch parallel known/unknown constrained Bayesian optimization with feasibility classification and its applications in computational fluid dynamics

DOI10.1016/j.cma.2018.12.033zbMath1440.76130OpenAlexW2907466830WikidataQ115734527 ScholiaQ115734527MaRDI QIDQ1987855

Yanyan Li

Publication date: 16 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2018.12.033

zbMATH Keywords

computational fluid dynamicsBayesian optimizationbatch parallelizationfeasibility classificationknown constraintunknown constraint

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Derivative-free methods and methods using generalized derivatives (90C56) Stochastic analysis applied to problems in fluid mechanics (76M35)

Related Items

Structural optimization of metamaterials based on periodic surface modeling ⋮ An asynchronous parallel high-throughput model calibration framework for crystal plasticity finite element constitutive models ⋮ Adaptive confidence bound based Bayesian optimization via potentially optimal Lipschitz conditions ⋮ Bayesian optimization package: PHYSBO ⋮ Black-Box Optimization: Methods and Applications ⋮ pBO-2GP-3B

Uses Software

• PARDISO
• DACE
• CMA-ES
• EGO
• DiceKriging
• DiceOptim
• Spearmint
• AdaBoost-SAMME

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