0375611 - ÚI 2012 RIV DE eng C - Conference Paper (international conference)
Pilát, Martin - Neruda, Roman
Local Meta-models for ASM-MOMA.
Advanced Intelligent Computing. Berlin: Springer, 2011 - (Huang, D.; Gan, Y.; Bevilacqua, V.; Figueroa, J.), s. 147-152. Lecture Notes in Computer Science, 6838. ISBN 978-3-642-24727-9. ISSN 0302-9743.
[ICIC 2011. International Conference on Intelligent Computing. Zhengzhou (CN), 11.08.2011-14.08.2011]
R&D Projects: GA MŠMT OC10047; GA ČR GD201/09/H057
Institutional research plan: CEZ:AV0Z10300504
Keywords : multiobjective optimization * meta-model * evolutionary algorithm
Subject RIV: IN - Informatics, Computer Science

Evolutionary algorithms generally require a large number of objective function evaluations which can be costly in practice. These evaluations can be replaced by evaluations of a cheaper meta-model of the objective functions. In this paper we describe a multiobjective memetic algorithm utilizing local distance based meta-models. This algorithm is evaluated and compared to standard multiobjective evolutionary algorithms as well as a similar algorithm with a global meta-model. The number of objective function evaluations is considered, and also the conditions under which the algorithm actually helps to reduce the time needed to find a solution are analyzed.
Permanent Link: http://hdl.handle.net/11104/0208215