Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions
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Publication:381435
DOI10.1007/s00158-009-0420-2zbMath1274.74291OpenAlexW2138002307MaRDI QIDQ381435
Publication date: 15 November 2013
Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00158-009-0420-2
approximationdesign optimizationhigh dimensionalmetamodelinglarge-scalesurrogateblack-box functioncomputationally-expensive
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Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
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- Optimization by Simulated Annealing
- Small sample sensitivity analysis techniques for computer models.with an application to risk assessment
- Exploratory designs for computational experiments
- A factorized high dimensional model representation on the nodes of a finite hyperprismatic regular grid
- Variable-complexity response surface approximations for wing structural weight in HSCT design
- A recursive algorithm for finding HDMR terms for sensitivity analysis
- Parallel radial basis function methods for the global optimization of expensive functions
- Additive regression and other nonparametric models
- Nonparametric Bayesian regression
- Multivariate adaptive regression splines
- Interaction spline models and their convergence rates
- Efficient global optimization of expensive black-box functions
- Orthogonal arrays. Theory and applications
- Lipschitzian optimization without the Lipschitz constant
- Quasi-regression
- A hypergraph framework for optimal model-based decomposition of design problems
- Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
- Bayesian-validated computer-simulation surrogates for optimization and design: Error estimates and applications
- A knowledge-based approach to response surface modelling in multifidelity optimization
- General foundations of high-dimensional model representations
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Bayesian experimental design: A review
- Efficient input-output model representations
- Global optimization in path synthesis based on design space reduction.
- Assessing linearity in high dimensions.
- A constraint mapping approach to the structural optimization of an expensive model using surrogates
- Quasi-regression with shrinkage
- An efficient algorithm for constructing optimal design of computer experiments
- Hybrid high dimensional model representation (HHDMR) on the partitioned data
- Bayesian Calibration of Computer Models
- Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming
- 10.1162/15324430152733142
- A Stochastic Radial Basis Function Method for the Global Optimization of Expensive Functions
- A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
- Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
- A Study of the Group Screening Method
- Two-Level Multifactor Designs for Detecting the Presence of Interactions
- Experimental Design: Review and Comment
- Algorithms for Computing the Sample Variance: Analysis and Recommendations
- A Trust Region Algorithm for Nonlinearly Constrained Optimization
- Efficiency of a Global Optimization Algorithm
- Recent Advances in Nonlinear Experimental Design
- Flexible Parsimonious Smoothing and Additive Modeling
- D-Optimality for Regression Designs: A Review
- Orthogonal Array-Based Latin Hypercubes
- Orthogonal Column Latin Hypercubes and Their Application in Computer Experiments
- A Pattern Search Filter Method for Nonlinear Programming without Derivatives
- Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
- A Fictitious Play Approach to Large-Scale Optimization
- Orthogonal Arrays of Strength two and three
- Stochastic Algorithms: Foundations and Applications
- High dimensional model representations generated from low dimensional data samples. I: mp-cut-HDMR
- Review of the space mapping approach for engineering optimization and modeling
- Metamodels for computer-based engineering design: Survey and recommendations
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