A Surrogate Multiobjective Evolutionary Strategy with Local Search and Pre-Selection

0380958 - ÚI 2013 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Pilát, M. - Neruda, Roman
A Surrogate Multiobjective Evolutionary Strategy with Local Search and Pre-Selection.
GECCO Companion '12. Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion. New York: ACM, 2012 - (Soule, T.), s. 633-634. ISBN 978-1-4503-1178-6.
[GECCO 2012. Genetic and Evolutionary Computation Conference. Conference on Genetic Algorithms /21./ and Annual Genetic Programming Conference /17./. Philadelphia (US), 07.07.2012-11.07.2012]
Grant CEP: GA MŠMT OC10047
Grant ostatní: GA UK(CZ) 345511
Institucionální podpora: RVO:67985807
Klíčová slova: multiobjective optimization * meta-model * evolutionary algorithm
Kód oboru RIV: IN - Informatika

In this paper we present an evolutionary strategy for multiobjective optimization. This evolution strategy is based on a surrogate memetic operator and a surrogate preselection model which provides several individuals in each generation. Thus, the optimization may be easily parallelized. The proposed algorithm is compared to some of existing evolutionary algorithms from the literature.
Trvalý link: http://hdl.handle.net/11104/0211542