Two-layer adaptive surrogate-assisted evolutionary algorithm for high-dimensional computationally expensive problems

• Published in: Journal of global optimization Vol. 74; no. 2; pp. 327 - 359
• Main Authors: Yang, Zan, Qiu, Haobo, Gao, Liang, Jiang, Chen, Zhang, Jinhao
• Format: Journal Article
• Language: English
• Published: New York Springer US 15.06.2019; Springer; Springer Nature B.V
• Subjects: Adaptive algorithms; Algorithms; Analysis; Computer Science; Evolutionary algorithms; Feedback; Genetic algorithms; Goal programming; Iterative methods; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Real Functions; Search methods; Strategy; Differential evolution; Dimension reduction technique; Surrogate-assisted evolutionary algorithms; Computationally expensive problems

Surrogate-assisted evolutionary algorithms (SAEAs) have recently shown excellent ability in solving computationally expensive optimization problems. However, with the increase of dimensions of research problems, the effectiveness of SAEAs for high-dimensional problems still needs to be improved furt...