Expected improvement for expensive optimization: a review
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Publication:2022176
DOI10.1007/s10898-020-00923-xzbMath1465.90104OpenAlexW3042036888MaRDI QIDQ2022176
Publication date: 28 April 2021
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10898-020-00923-x
constrained optimizationmultiobjective optimizationparallel computingnoisy optimizationexpected improvementmulti-fidelity optimization
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Uses Software
Cites Work
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- Analysis of multi-objective Kriging-based methods for constrained global optimization
- A new expected-improvement algorithm for continuous minimax optimization
- Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations
- Min-median-max metamodel-based unconstrained nonlinear optimization problems
- Constrained efficient global optimization with support vector machines
- Expected improvement in efficient global optimization through bootstrapped Kriging
- Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization
- Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for~computationally expensive black-box global optimization problems
- A Bayesian approach to constrained single- and multi-objective optimization
- Balancing global and local search in parallel efficient global optimization algorithms
- Constrained global optimization of expensive black box functions using radial basis functions
- Sequential design of computer experiments for the estimation of a probability of failure
- Branch and bound algorithms for maximizing expected improvement functions
- Nash game based efficient global optimization for large-scale design problems
- On the design of optimization strategies based on global response surface approximation models
- An informational approach to the global optimization of expensive-to-evaluate functions
- Computational intelligence in expensive optimization problems
- Kriging-based infill sampling criterion for constraint handling in multi-objective optimization
- An adaptive radial basis algorithm (ARBF) for expensive black-box global optimization
- Convergence properties of the expected improvement algorithm with fixed mean and covariance functions
- Kriging metamodeling in simulation: a review
- Global optimization of expensive-to-evaluate functions: An empirical comparison of two sampling criteria
- Efficient global optimization of expensive black-box functions
- A knowledge-based approach to response surface modelling in multifidelity optimization
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Multiobjective optimization of expensive-to-evaluate deterministic computer simulator models
- The design and analysis of computer experiments
- Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise
- A taxonomy of global optimization methods based on response surfaces
- Compactly supported correlation functions
- On the choice of the low-dimensional domain for global optimization via random embeddings
- A supermartingale approach to Gaussian process based sequential design of experiments
- A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization
- Efficient global optimization algorithm assisted by multiple surrogate techniques
- Examples of inconsistency in optimization by expected improvement
- Pseudo expected improvement criterion for parallel EGO algorithm
- Extended co-Kriging interpolation method based on multi-fidelity data
- Two-layer adaptive surrogate-assisted evolutionary algorithm for high-dimensional computationally expensive problems
- Global optimization of stochastic black-box systems via sequential kriging meta-models
- Bayesian Optimization in a Billion Dimensions via Random Embeddings
- The Knowledge-Gradient Policy for Correlated Normal Beliefs
- Bayesian Adaptive Reconstruction of Profile Optima and Optimizers
- On the Convergence Rates of Expected Improvement Methods
- A Multicriteria Generalization of Bayesian Global Optimization
- A Knowledge-Gradient Policy for Sequential Information Collection
- Multi-fidelity optimization via surrogate modelling
- Predicting the output from a complex computer code when fast approximations are available
- Efficient global optimization for high-dimensional constrained problems by using the Kriging models combined with the partial least squares method
- Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time
- Convergence rates of efficient global optimization algorithms
- Evolutionary Multi-Criterion Optimization
- A radial basis function method for global optimization
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