Multi co-objective evolutionary optimization : cross surrogate augmentation for computationally expensive problems
In this paper, we present a novel cross-surrogate assisted memetic algorithm (CSAMA) as a manifestation of multi co-objective evolutionary computation to enhance the search on computationally expensive problems by means of transferring, sharing and reusing information across objectives. In particula...
Saved in:
Main Authors: | Le, Minh Nghia, Ong, Yew Soon, Menzel, Stefan, Seah, Chun-Wei, Sendhoff, Bernhard |
---|---|
Other Authors: | School of Computer Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/102007 http://hdl.handle.net/10220/12022 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Evolution by adapting surrogates
by: Ong, Yew Soon, et al.
Published: (2014) -
Multiproblem surrogates : transfer evolutionary multiobjective optimization of computationally expensive problems
by: Tan, Alan Wei Ming, et al.
Published: (2020) -
Generalizing surrogate-assisted evolutionary computation
by: Lim, Dudy, et al.
Published: (2021) -
Evolutionary optimization of expensive multiobjective problems with co-sub-Pareto front Gaussian process surrogates
by: Luo, Jianping, et al.
Published: (2021) -
Evolutionary optimization for computationally expensive problems
by: Lim, Dudy
Published: (2009)