The Effect of Different Local Search Algorithms on the Performance of Multi-Objective Optimizers

0435894 - ÚI 2015 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Pilát, M. - Neruda, Roman
The Effect of Different Local Search Algorithms on the Performance of Multi-Objective Optimizers.
2014 IEEE Congress on Evolutionary Computation. Piscataway: IEEE CS, 2014, s. 2172-2179. ISBN 978-1-4799-6626-4.
[CEC 2014. IEEE Congress on Evolutionary Computation. Beijing (CN), 06.06.2014-11.06.2014]
Grant CEP: GA MŠMT(CZ) LD13002
Grant ostatní: SVV(CZ) 260 104
Institucionální podpora: RVO:67985807
Klíčová slova: evolutionary computation * optimisation * search problems
Kód oboru RIV: IN - Informatika

Several contemporary multi-objective surrogatebased algorithms use some kind of local search operator. The search technique used in this operator can largely affect the performance of the multi-objective optimizer as a whole, however, little attention is often paid to the selection of this technique. In this paper, we compare three different local search techniques and evaluate their effect on the performance of two different surrogate based multi-objective optimizers. The algorithms are evaluated using the well known ZDT and WFG benchmark suites and recommendations are made based on the results.
Trvalý link: http://hdl.handle.net/11104/0239722