Surrogate-based Genetic Algorithms
Surrogate-Based Genetic Algorithms is a type of genetic algorithm that incorporates surrogate models to approximate fitness evaluations, thereby reducing the computational cost of optimization by guiding the search process with predictions from the surrogate.
38
Publications
2.6K
Citations
98
Authors
59
Institutions
Publications per year
2017–2026
23
38
1–5 of 38
98
Universidade Federal de Juiz de Fora, Brazil
3 publications · 53 citations
3
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Laboratório Nacional de Computação Científica, Brazil
3 publications · 53 citations
3
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2
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2
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2
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1–5 of 98
59
Laboratório Nacional de Computação Científica
Petrópolis, Brazil
3 h-index
5 publications
87 citations

Huazhong University of Science and Technology
Wuhan, China
3 h-index
12 publications
583 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
215 citations

Universidade Federal de Juiz de Fora
Juiz de Fora, Brazil
3 h-index
3 publications
53 citations
Centrum Wiskunde & Informatica
Amsterdam, The Netherlands
2 h-index
3 publications
51 citations

University of Surrey
Guildford, United Kingdom
2 h-index
2 publications
1.5K citations

Delft University of Technology
Delft, The Netherlands
2 h-index
2 publications
37 citations

Halmstad University
Halmstad, Sweden
2 h-index
8 publications
272 citations
1–8 of 59
3 publications · 87 citations
3
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2 publications · 80 citations
2
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2 publications · 1.5K citations
2
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2 publications · 123 citations
2
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2 publications · 79 citations
2
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