Recent advances in Bayesian optimization
Bayesian optimization has emerged at the forefront of expensive black-box optimization due
to its data efficiency. Recent years have witnessed a proliferation of studies on the …
to its data efficiency. Recent years have witnessed a proliferation of studies on the …
Automated algorithm selection: Survey and perspectives
It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …
intensely studied, different instances are best solved using different algorithms. This is …
Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey
H Khatouri, T Benamara, P Breitkopf… - Advanced Modeling and …, 2022 - Springer
In design optimization of complex systems, the surrogate model approach relying on
progressively enriched Design of Experiments (DOE) avoids efficiency problems …
progressively enriched Design of Experiments (DOE) avoids efficiency problems …
Constrained efficient global optimization of expensive black-box functions
We study the problem of constrained efficient global optimization, where both the objective
and constraints are expensive black-box functions that can be learned with Gaussian …
and constraints are expensive black-box functions that can be learned with Gaussian …
A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization
Expected improvement (EI) is a popular infill criterion in Gaussian process assisted
optimization of expensive problems for determining which candidate solution is to be …
optimization of expensive problems for determining which candidate solution is to be …
Feasibility/Flexibility-based optimization for process design and operations
This paper provides an overview of concepts and computational approaches for the
evaluation of feasibility/flexibility and how they can be used for process design and process …
evaluation of feasibility/flexibility and how they can be used for process design and process …
On the use of surrogate models in engineering design optimization and exploration: The key issues
Surrogate models are invaluable tools that greatly assist the process of computationally
expensive analyses and optimization. Engineering optimization reaps the benefit from …
expensive analyses and optimization. Engineering optimization reaps the benefit from …
A Generator of Multiextremal Test Classes With Known Solutions for Black-Box-Constrained Global Optimization
YD Sergeyev, DE Kvasov… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A generator of classes of multidimensional test problems for benchmarking continuous
constrained global optimization methods is proposed. It is based on the generator of test …
constrained global optimization methods is proposed. It is based on the generator of test …
Constrained optimization of black-box stochastic systems using a novel feasibility enhanced Kriging-based method
Z Wang, M Ierapetritou - Computers & Chemical Engineering, 2018 - Elsevier
Stochastically constrained simulation optimization problems are challenging because the
inherent noise terms to a black-box system lead to the need of considering the uncertainty at …
inherent noise terms to a black-box system lead to the need of considering the uncertainty at …
Investigating the correlation amongst the objective and constraints in Gaussian process-assisted highly constrained expensive optimization
Expensive constrained optimization refers to problems where the calculation of the objective
and/or constraint functions are computationally intensive due to the involvement of complex …
and/or constraint functions are computationally intensive due to the involvement of complex …