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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Main Authors: | , , , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
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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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