A Surrogate-Assisted Gray Prediction Evolution Algorithm for High-Dimensional Expensive Optimization Problems
Surrogate-assisted evolutionary algorithms (SAEAs), which combine the search capabilities of evolutionary algorithms (EAs) with the predictive capabilities of surrogate models, are effective methods for solving expensive optimization problems (EOPs). However, the over-reliance on the accuracy of the...
Saved in:
| Main Authors: | Xiaoliang Huang, Hongbing Liu, Quan Zhou, Qinghua Su |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/6/1007 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems
by: Hanqing Liu, et al.
Published: (2025-04-01) -
Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems
by: Xiangyong Liu, et al.
Published: (2025-01-01) -
A Preference Model-Based Surrogate-Assisted Constrained Multi-Objective Evolutionary Algorithm for Expensively Constrained Multi-Objective Problems
by: Yu Sun, et al.
Published: (2025-04-01) -
A classifier-assisted evolutionary algorithm with knowledge transfer for expensive multitasking problems
by: Min Hu, et al.
Published: (2025-05-01) -
A gradient-descent-like learning-based framework in surrogate-assisted evolutionary algorithms for expensive many-objective optimization
by: Chaoyi Sun, et al.
Published: (2025-06-01)