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

0380958 - ÚI 2013 RIV US eng C - Conference Paper (international conference)
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]
R&D Projects: GA MŠMT OC10047
Grant - others:GA UK(CZ) 345511
Institutional support: RVO:67985807
Keywords : multiobjective optimization * meta-model * evolutionary algorithm
Subject RIV: IN - Informatics, Computer Science

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.
Permanent Link: http://hdl.handle.net/11104/0211542