Efficient evolutionary optimization algorithm : filtered differential evolution
Julkaistu sarjassa
Jyväskylän yliopisto. Reports of the Department of Mathematical Information Technology. Series B. Scientific computingTekijät
Päivämäärä
2008
2022:24 | 2023:42 | 2024:34 | 2025:2
Solving many real-life engineering problems requires often global and efficient (in terms of objective function evaluations) treatment, because function values involved are produced via time consuming simulations. In this study, we consider optimization problems of this type by discussing some drawbacks of the current surrogate assisted methods and then introduce a new population based optimization algorithm, which borrows features of the well-known Differential Evolution algorithm, but improves its efficiency by filtering away ineffective trial points.
ISBN
978-951-39-9036-7Metadata
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- Digitoidut julkaisut [274]
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