Surrogate-assisted autoencoder-embedded evolutionary optimization algorithm to solve high-dimensional expensive problems
Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve
computationally expensive problems with some success. However, traditional EAs are not …
computationally expensive problems with some success. However, traditional EAs are not …
Expensive optimization via surrogate-assisted and model-free evolutionary optimization
The surrogate-assisted evolutionary algorithm (SAEA) is one of the most efficient
approaches for solving expensive optimization problems. However, it still faces challenges …
approaches for solving expensive optimization problems. However, it still faces challenges …
A Gaussian process surrogate model assisted evolutionary algorithm for medium scale expensive optimization problems
Surrogate model assisted evolutionary algorithms (SAEAs) have recently attracted much
attention due to the growing need for computationally expensive optimization in many real …
attention due to the growing need for computationally expensive optimization in many real …
Two-stage data-driven evolutionary optimization for high-dimensional expensive problems
Surrogate-assisted evolutionary algorithms (SAEAs) have been widely used for solving
complex and computationally expensive optimization problems. However, most of the …
complex and computationally expensive optimization problems. However, most of the …
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 …
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 …
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 …
A novel evolutionary sampling assisted optimization method for high-dimensional expensive problems
X Wang, GG Wang, B Song, P Wang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Surrogate-assisted evolutionary algorithms (SAEAs) are promising methods for solving high-
dimensional expensive problems. The basic idea of SAEAs is the integration of nature …
dimensional expensive problems. The basic idea of SAEAs is the integration of nature …
Surrogate-assisted differential evolution with adaptive multisubspace search for large-scale expensive optimization
Real-world industrial engineering optimization problems often have a large number of
decision variables. Most existing large-scale evolutionary algorithms (EAs) need a large …
decision variables. Most existing large-scale evolutionary algorithms (EAs) need a large …
A review of surrogate-assisted evolutionary algorithms for expensive optimization problems
C He, Y Zhang, D Gong, X Ji - Expert Systems with Applications, 2023 - Elsevier
Many problems in real life can be seen as Expensive Optimization Problems (EOPs).
Compared with traditional optimization problems, the evaluation cost of candidate solutions …
Compared with traditional optimization problems, the evaluation cost of candidate solutions …