An Adaptive Exploration-Exploitation Algorithm for Constructing Metamodels in Random Simulation Using a Novel Sequential Experimental Design
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Publication:5415896
DOI10.1080/03610918.2012.720743zbMath1291.62142OpenAlexW1982672995MaRDI QIDQ5415896
Publication date: 19 May 2014
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2012.720743
response surfaceKrigingmetamodelsimulation optimizationsequential designexplorative-exploitative search
Sequential statistical design (62L05) Probabilistic methods, stochastic differential equations (65C99)
Related Items (6)
Sequential design strategies for mean response surface metamodeling via stochastic kriging with adaptive exploration and exploitation ⋮ Gradient and uncertainty enhanced sequential sampling for global fit ⋮ Some Monotonicity Results for Stochastic Kriging Metamodels in Sequential Settings ⋮ Multivariate function approximations using the D-MORPH algorithm ⋮ Incremental modeling of a new high-order polynomial surrogate model ⋮ A Fuzzy Hybrid Sequential Design Strategy for Global Surrogate Modeling of High-Dimensional Computer Experiments
Uses Software
Cites Work
- Constrained optimization in expensive simulation: novel approach
- Efficient global optimization of expensive black-box functions
- A sequential-design metamodeling strategy for simulation optimization
- Batch sequential designs for computer experiments
- Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping
- Application-driven sequential designs for simulation experiments: Kriging metamodelling
- Hierarchical Nonlinear Approximation for Experimental Design and Statistical Data Fitting
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