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

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...

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書目詳細資料
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
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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