[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …
world applications. However, their inherent complexity, coupled with the curse of …
Multi-surrogate assisted binary particle swarm optimization algorithm and its application for feature selection
The evolutionary algorithms (EAs) have been shown favorable performance for feature
selection. However, a large number of evaluations are required through the EAs. Thus, they …
selection. However, a large number of evaluations are required through the EAs. Thus, they …
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 …
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 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 …
An adaptive stochastic dominant learning swarm optimizer for high-dimensional optimization
High-dimensional problems are ubiquitous in many fields, yet still remain challenging to be
solved. To tackle such problems with high effectiveness and efficiency, this article proposes …
solved. To tackle such problems with high effectiveness and efficiency, this article proposes …
A velocity-based butterfly optimization algorithm for high-dimensional optimization and feature selection
W Long, M Xu, J Jiao, T Wu, M Tang, S Cai - Expert Systems with …, 2022 - Elsevier
Throughout the last decade, high-dimensional function optimization problems have received
substantial research interest in the field of intelligence computation. Butterfly optimization …
substantial research interest in the field of intelligence computation. Butterfly optimization …
Linear subspace surrogate modeling for large-scale expensive single/multi-objective optimization
Despite that the surrogate-assisted evolutionary algorithms have achieved great success in
addressing expensive optimization problems, they still suffer from stiff challenges when the …
addressing expensive optimization problems, they still suffer from stiff challenges when the …
Hybrid whale optimization algorithm with gathering strategies for high-dimensional problems
X Zhang, S Wen - Expert Systems with Applications, 2021 - Elsevier
In order to solve the problems, such as insufficient search ability and low search efficiency,
of Whale Optimization Algorithm (WOA) in solving high-dimensional problems, a novel …
of Whale Optimization Algorithm (WOA) in solving high-dimensional problems, a novel …
Cooperative coevolutionary surrogate ensemble-assisted differential evolution with efficient dual differential grou** for large-scale expensive optimization problems
This paper proposes a novel algorithm named surrogate ensemble assisted differential
evolution with efficient dual differential grou** (SEADECC-EDDG) to deal with large-scale …
evolution with efficient dual differential grou** (SEADECC-EDDG) to deal with large-scale …