Kriging metamodeling in simulation: a review
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Publication:1011208
DOI10.1016/j.ejor.2007.10.013zbMath1157.90544OpenAlexW3122455945MaRDI QIDQ1011208
Publication date: 8 April 2009
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://research.tilburguniversity.edu/en/publications/29d6926e-c381-4b58-ae58-87116856e27c
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Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Statistical testing of optimality conditions in multiresponse simulation-based optimization
- Efficient global optimization of expensive black-box functions
- The design and analysis of computer experiments.
- A methodology for fitting and validating metamodels in simulation
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Bayesian experimental design: A review
- Robustness of kriging when interpolating in random simulation with heterogeneous variances: some experiments
- Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping
- Global optimization of stochastic black-box systems via sequential kriging meta-models
- Comparison of designs for computer experiments
- Kriging for interpolation in random simulation
- The correct Kriging variance estimated by bootstrapping
- Estimating Percentiles of Uncertain Computer Code Outputs
- Application-driven sequential designs for simulation experiments: Kriging metamodelling
- Design and analysis of simulation experiments
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