An efficient surrogate-assisted hybrid optimization algorithm for expensive optimization problems
Surrogate-assisted evolutionary algorithms (SAEAs) are potential approaches to solve
computationally expensive optimization problems. The critical idea of SAEAs is to combine …
computationally expensive optimization problems. The critical idea of SAEAs is to combine …
Evolutionary optimization methods for high-dimensional expensive problems: A survey
Evolutionary computation is a rapidly evolving field and the related algorithms have been
successfully used to solve various real-world optimization problems. The past decade has …
successfully used to solve various real-world optimization problems. The past decade has …
A radial basis function surrogate model assisted evolutionary algorithm for high-dimensional expensive optimization problems
Evolutionary algorithms require large number of function evaluations to locate the global
optimum, making it computationally prohibitive on dealing with expensive problems …
optimum, making it computationally prohibitive on dealing with expensive problems …
Surrogate-assisted evolutionary optimisation: a novel blueprint and a state of the art survey
MIE Khaldi, A Draa - Evolutionary Intelligence, 2023 - Springer
Abstract Surrogate-Assisted Evolutionary Optimisation algorithms are a specialized brand of
optimisers developed to undertake problems with computationally expensive fitness …
optimisers developed to undertake problems with computationally expensive fitness …
A surrogate-assisted multiswarm optimization algorithm for high-dimensional computationally expensive problems
This article presents a surrogate-assisted multiswarm optimization (SAMSO) algorithm for
high-dimensional computationally expensive problems. The proposed algorithm includes …
high-dimensional computationally expensive problems. The proposed algorithm includes …
A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems
Q Gu, Q Wang, X Li, X Li - Knowledge-Based Systems, 2021 - Elsevier
Surrogate-assisted evolutionary algorithms have been commonly used in extremely
expensive optimization problems. However, many existing algorithms are only significantly …
expensive optimization problems. However, many existing algorithms are only significantly …
A multi-strategy surrogate-assisted competitive swarm optimizer for expensive optimization problems
Evolutionary computation is a powerful tool for solving nonconvex optimization problems.
Generally, evolutionary algorithms take numerous fitness evaluations to obtain the potential …
Generally, evolutionary algorithms take numerous fitness evaluations to obtain the potential …
A bi-population cooperative optimization algorithm assisted by an autoencoder for medium-scale expensive problems
This study presents an autoencoder-embedded optimization (AEO) algorithm which involves
a bi-population cooperative strategy for medium-scale expensive problems (MEPs). A huge …
a bi-population cooperative strategy for medium-scale expensive problems (MEPs). A huge …
Efficient hierarchical surrogate-assisted differential evolution for high-dimensional expensive optimization
Surrogate-assisted evolutionary algorithms have gained increasingly attention due to the
promising search capabilities for solving computationally expensive optimization problems …
promising search capabilities for solving computationally expensive optimization problems …
Global and local surrogate-model-assisted differential evolution for waterflooding production optimization
Surrogate models, which have become a popular approach to oil‐reservoir production‐
optimization problems, use a computationally inexpensive approximation function to replace …
optimization problems, use a computationally inexpensive approximation function to replace …