Evolutionary optimization of expensive multiobjective problems with co-sub-Pareto front Gaussian process surrogates
This paper proposes a Gaussian process (GP) based co-sub-Pareto front surrogate augmentation strategy for evolutionary optimization of computationally expensive multiobjective problems. In the proposed algorithm, a multiobjective problem is decomposed into a number of subproblems, the solution of ea...
Main Authors: | Luo, Jianping, Gupta, Abhishek, Ong, Yew-Soon, Wang, Zhenkun |
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Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/150433 |
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