Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys

Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys Full article

Conference

GECCO: Genetic and Evolutionary Computation Conference
10-14 Jul 2021 , Lille

Source

Proceedings of the Genetic and Evolutionary Computation Conference
Compilation, 2021. ISBN 978-1-4503-8350-9.

Output data

Year: 2021, Pages: 1133 - 1141 Pages count : 9 DOI: 10.1145/3449639.3459398

Authors

Dang Duc-Cuong ¹ , Eremeev Anton ^2,4 , Lehre Per Kristian ³

Affiliations

1	University of Southampton, Southampton, United Kingdom
2	Sobolev Institute of Mathematics, Novosibirsk, Russia
3	University of Birmingham, Birmingham, United Kingdom
4	INION RAS, Moscow, Russia

Dang D-C. , Eremeev A. , Lehre P.K.
Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys
In compilation Proceedings of the Genetic and Evolutionary Computation Conference. 2021. – C.1133 - 1141. – ISBN 978-1-4503-8350-9. DOI: 10.1145/3449639.3459398 OpenAlex

Published print:

Jun 21, 2021

OpenAlex:

W3162553722

DB	Citing
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