In this paper, two sets of subproblems are op-timized, assisted by surrogate models, to collaboratively explore the optimal solution space for large-scale ...
In this paper, two sets of subproblems are op- timized, assisted by surrogate models, to collaboratively explore the optimal solution space for large-scale ...
Experimental findings on 15 CEC2013 benchmark problems show that the proposed approach outperforms four state-of-the-art algorithms in solving expensive ...
Surrogate-Assisted Particle Swarm Optimization with Dual-Subspace Search for Large-Scale Expensive Optimization. June 2024. DOI:10.1109/CEC60901.2024.10611757.
Jun 27, 2024 · This approach leverages both restricted Boltzmann machines (RBMs) for feature learning and reinforcement learning for adaptive strategy selection.
Aug 12, 2021 · A surrogate-assisted learning strategy-based particle swarm optimizer is proposed for guiding the search of each subswarm. Furthermore, a model ...
A surrogate-assisted competitive swarm optimizer (SACSO) is proposed to exploit the potential of evolutionary algorithms to handle expensive optimization ...
Missing: Dual- | Show results with:Dual-
Extensive comparisons with several state-of-the-art algorithms on two widely used sets of large-scale benchmark functions confirm the competitive performance of ...
Dec 6, 2022 · To address this challenge, surrogate-assisted EAs based on the divide-and-conquer strategy have been proposed and shown to be promising.
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May 18, 2024 · This paper conducts a comprehensive survey on SAEAs tailored to address ECOPs. This survey comprises two primary segments.