2 citations · 4 across the 4 of their papers we have counts for
8 papers · 1 filter
Enhancing hierarchical surrogate-assisted evolutionary algorithm for high-dimensional expensive optimization via random projection
Xiaodong Ren, Daofu Guo, Zhigang Ren +2
By remarkably reducing real fitness evaluations, surrogate-assisted evolutionary algorithms (SAEAs), especially hierarchical SAEAs, have been shown to be effective in solving compu…
A Surrogate-Assisted Variable Grouping Algorithm for General Large Scale Global Optimization Problems
An Chen, Zhigang Ren, Muyi Wang +3
Problem decomposition plays a vital role when applying cooperative coevolution (CC) to large scale global optimization problems. However, most learning-based decomposition algorith…
An Eigenspace Divide-and-Conquer Approach for Large-Scale Optimization
Zhigang Ren, Yongsheng Liang, Muyi Wang +2
Divide-and-conquer-based (DC-based) evolutionary algorithms (EAs) have achieved notable success in dealing with large-scale optimization problems (LSOPs). However, the appealing pe…
Niching an Archive-based Gaussian Estimation of Distribution Algorithm via Adaptive Clustering
Yongsheng Liang, Zhigang Ren, Bei Pang +1
As a model-based evolutionary algorithm, estimation of distribution algorithm (EDA) possesses unique characteristics and has been widely applied to global optimization. However, tr…
Enhancing Cooperative Coevolution for Large Scale Optimization by Adaptively Constructing Surrogate Models
Bei Pang, Zhigang Ren, Yongsheng Liang +1
It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a divide-and-conquer strategy. However, its performa…
A Global Information Based Adaptive Threshold for Grouping Large Scale Global Optimization Problems
An Chen, Yipeng Zhang, Zhigang Ren +2
By taking the idea of divide-and-conquer, cooperative coevolution (CC) provides a powerful architecture for large scale global optimization (LSGO) problems, but its efficiency reli…