Surrogate-assisted bounding-box approach for optimization problems with tunable objectives fidelity

DOI10.1007/s10898-019-00823-9zbMath1432.90097OpenAlexW2970170808MaRDI QIDQ2010110

M. Rivier, Pietro Marco Congedo

Publication date: 3 December 2019

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

Full work available at URL: https://hal.inria.fr/hal-01713043v5/file/RR-9155.pdf

zbMATH Keywords

multi-objective optimizationuncertainty-based optimizationerror bounding-boxessurrogate-assisting strategytunable fidelity

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Stochastic programming (90C15)

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Cites Work

• An adaptive strategy on the error of the objective functions for uncertainty-based derivative-free optimization
• Approximate implementations of pure random search in the presence of noise
• Comparing solutions under uncertainty in multiobjective optimization
• Stratified Bayesian optimization
• Simulated annealing for noisy cost functions
• On similarities between two models of global optimization: Statistical models and radial basis functions
• Evolutionary Multi-Criterion Optimization

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