Sequential model based optimization of partially defined functions under unknown constraints
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Publication:2022235
DOI10.1007/s10898-019-00860-4zbMath1465.90068OpenAlexW2990956201WikidataQ126647073 ScholiaQ126647073MaRDI QIDQ2022235
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/s10898-019-00860-4
constrained global optimizationpartially defined objective functionssequential model based optimization
Related Items (4)
SMGO-\(\Delta\): balancing caution and reward in global optimization with black-box constraints ⋮ Preface to the special issue dedicated to the 14th international workshop on global optimization held in Leiden, the Netherlands, September 18--21, 2018 ⋮ A new \texttt{DIRECT-GLh} algorithm for global optimization with hidden constraints ⋮ Handling of Constraints in Efficient Global Optimization
Uses Software
Cites Work
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- Constrained efficient global optimization with support vector machines
- A Bayesian approach to constrained single- and multi-objective optimization
- A probabilistic algorithm for global optimization
- Efficient global optimization of expensive black-box functions
- Index information algorithm with local tuning for solving multidimensional global optimization problems with multiextremal constraints
- Global optimization based on a statistical model and simplicial partitioning.
- Constrained Bayesian optimization with noisy experiments
- Bayesian optimization of pump operations in water distribution systems
- A derivative-free algorithm for constrained global optimization based on exact penalty functions
- A DIRECT-type approach for derivative-free constrained global optimization
- A one-dimensional local tuning algorithm for solving GO problems with partially defined constraints
- Stochastic global optimization.
- Global optimization of stochastic black-box systems via sequential kriging meta-models
- Introduction to Global Optimization Exploiting Space-Filling Curves
- Support Vector Machines
- On optimizing certain nonlinear convex functions which are partially defined by a simulation process
- Exact Penalty Functions in Constrained Optimization
- Deterministic Global Optimization
- Bayesian Optimization and Data Science
- Pitfalls and Best Practices in Algorithm Configuration
- Advantages of simplicial partitioning for Lipschitz optimization problems with linear constraints
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