Pages that link to "Item:Q2392755"
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The following pages link to Efficient global optimization algorithm assisted by multiple surrogate techniques (Q2392755):
Displaying 32 items.
- Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO (Q322958) (← links)
- Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for~computationally expensive black-box global optimization problems (Q486382) (← links)
- Global optimization of general constrained grey-box models: new method and its application to constrained PDEs for pressure swing adsorption (Q506438) (← links)
- Balancing global and local search in parallel efficient global optimization algorithms (Q522283) (← links)
- SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems (Q727388) (← links)
- Order-based error for managing ensembles of surrogates in mesh adaptive direct search (Q1704921) (← links)
- Scalable Gaussian process-based transfer surrogates for hyperparameter optimization (Q1707465) (← links)
- Setting targets for surrogate-based optimization (Q1942023) (← links)
- Filter-based adaptive Kriging method for black-box optimization problems with expensive objective and constraints (Q1987853) (← links)
- Machine-learning in optimization of expensive black-box functions (Q2012143) (← links)
- Expected improvement for expensive optimization: a review (Q2022176) (← links)
- Batch sequential adaptive designs for global optimization (Q2089024) (← links)
- Interval uncertainty propagation by a parallel Bayesian global optimization method (Q2109600) (← links)
- A fully adaptive method for structural stochastic response analysis based on direct probability integral method (Q2156774) (← links)
- Quantifying uncertainty with ensembles of surrogates for blackbox optimization (Q2162525) (← links)
- Enhanced variable-fidelity surrogate-based optimization framework by Gaussian process regression and fuzzy clustering (Q2184447) (← links)
- A surrogate-based cooperative optimization framework for computationally expensive black-box problems (Q2218881) (← links)
- Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian processes (Q2237721) (← links)
- Bayesian optimization using deep Gaussian processes with applications to aerospace system design (Q2245694) (← links)
- ARGONAUT: algorithms for global optimization of constrained grey-box computational problems (Q2359400) (← links)
- Pseudo expected improvement criterion for parallel EGO algorithm (Q2399490) (← links)
- Two-layer adaptive surrogate-assisted evolutionary algorithm for high-dimensional computationally expensive problems (Q2423810) (← links)
- An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization (Q2660961) (← links)
- Evolutionary model type selection for global surrogate modeling (Q2880961) (← links)
- Comparison for two global optimization algorithms based on Kriging surrogate model (Q2992267) (← links)
- Universal Prediction Distribution for Surrogate Models (Q4636353) (← links)
- Surrogate‐based methods for black‐box optimization (Q5278217) (← links)
- Purposeful cross-validation: a novel cross-validation strategy for improved surrogate optimizability (Q6048037) (← links)
- Adaptive kriging-assisted optimization of low-thrust many-revolution transfers to geostationary Earth orbit (Q6048065) (← links)
- A novel sampling method for adaptive gradient-enhanced kriging (Q6118505) (← links)
- A kriging-assisted bi-objective constrained global optimization algorithm for expensive constrained optimization problems (Q6191893) (← links)
- Adaptive multi-surrogate-based constrained optimization method and its application (Q6554058) (← links)
