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

0435894 - ÚI 2015 RIV US eng C - Conference Paper (international conference)
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]
R&D Projects: GA MŠMT(CZ) LD13002
Grant - others:SVV(CZ) 260 104
Institutional support: RVO:67985807
Keywords : evolutionary computation * optimisation * search problems
Subject RIV: IN - Informatics, Computer Science

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.
Permanent Link: http://hdl.handle.net/11104/0239722