Multi co-objective evolutionary optimization : cross surrogate augmentation for computationally expensive problems

• Main Authors: Le, Minh Nghia, Ong, Yew Soon, Menzel, Stefan, Seah, Chun-Wei, Sendhoff, Bernhard
• 其他作者: School of Computer Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2013
• 主題: DRNTU::Engineering::Computer science and engineering
• 在線閱讀: https://hdl.handle.net/10356/102007; http://hdl.handle.net/10220/12022

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...