Surrogate-Assisted Evolutionary Optimisation (SAEOpt'16) Chairs' Welcome & Organization
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- Surrogate-Assisted Evolutionary Optimisation (SAEOpt'16) Chairs' Welcome & Organization
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Surrogate-assisted evolutionary programming for high dimensional constrained black-box optimization
GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computationThis paper presents a novel surrogate-assisted evolutionary programming (EP) method for high dimensional constrained black-box optimization with many black-box inequality constraints. A cubic radial basis function (RBF) surrogate is used and the ...
Generalizing surrogate-assisted evolutionary computation
Using surrogate models in evolutionary search provides an efficient means of handling today's complex applications plagued with increasing high-computational needs. Recent surrogate-assisted evolutionary frameworks have relied on the use of a variety of ...
Surrogate-Assisted Partial Order-Based Evolutionary Optimisation
EMO 2017: 9th International Conference on Evolutionary Multi-Criterion Optimization - Volume 10173In this paper, we propose a novel approach SAPEO to support the survival selection process in evolutionary multi-objective algorithms with surrogate models. The approach dynamically chooses individuals to evaluate exactly based on the model uncertainty ...
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- Editor:
- Tobias Friedrich,
- General Chair:
- Frank Neumann,
- Program Chair:
- Andrew M. Sutton
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Association for Computing Machinery
New York, NY, United States
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- Engineering and Physical Sciences Research Council UK
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