Efficient evolutionary optimization algorithm : filtered differential evolution
Abstract
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.
Main Author
Format
Books
Book
Published
2008
Series
ISBN
978-951-39-9036-7
The permanent address of the publication
https://urn.fi/URN:ISBN:978-951-39-9036-7Käytä tätä linkitykseen.
Language
English
Published in
Jyväskylän yliopisto. Reports of the Department of Mathematical Information Technology. Series B. Scientific computing
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