A robust multi-objective Bayesian optimization framework considering input uncertainty

DOI10.1007/s10898-022-01262-9zbMath1530.90094arXiv2202.12848OpenAlexW4311923925MaRDI QIDQ6173962

Jixiang Qing, Ivo Couckuyt, Tom Dhaene

Publication date: 13 July 2023

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2202.12848

zbMATH Keywords

Gaussian processrobust optimizationefficient global optimizationBayesian optimization

Mathematics Subject Classification ID

Bayesian inference (62F15) Multi-objective and goal programming (90C29) Nonlinear programming (90C30) Stochastic programming (90C15) Robustness in mathematical programming (90C17)

Cites Work

• Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization
• Computing a nearest symmetric positive semidefinite matrix
• Efficient global optimization of expensive black-box functions
• Efficient computation of expected hypervolume improvement using box decomposition algorithms
• The Sample Average Approximation Method for Stochastic Discrete Optimization
• Advanced Lectures on Machine Learning
• Evolutionary Multi-Criterion Optimization

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