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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Bibliographic Details
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
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Institution: Nanyang Technological University
Language: English
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