Combining Multiobjective and Single-Objective Genetic Algorithms in Heterogeneous Island Model

0358846 - ÚI 2012 RIV US eng C - Conference Paper (international conference)
Pilát, M. - Neruda, Roman
Combining Multiobjective and Single-Objective Genetic Algorithms in Heterogeneous Island Model.
CEC 2010. Proceedings of the IEEE Congress on Evolutionary Computation. Piscataway: IEEE, 2010, s. 1-8. ISBN 978-1-4244-6910-9.
[WCCI 2010. IEEE World Congress on Computational Intelligence. Barcelona (ES), 18.07.2010-23.07.2010]
R&D Projects: GA MŠMT OC10047
Institutional research plan: CEZ:AV0Z10300504
Keywords : multiobjective optimization * single-objective optimization * genetic algorithms * island model * hybrid model
Subject RIV: IN - Informatics, Computer Science

The majority of multiobjective genetic algorithms is computationally expensive, therefore they often need to be parallelized before they can be used to solve practical tasks. Parallelization of multiobjective genetic algorithms is a relatively studied area, but no clearly winning approach has appeared yet. In this paper we present a novel parallel hybrid algorithm which combines multiobjective and single-objective genetic algorithms. We how that this algorithm can be successfully used to solve multiobjective optimization problems while outperforming more traditional parallel versions of multiobjective genetic algorithms.
Permanent Link: http://hdl.handle.net/11104/0196771