par Aydin, Dogan;Liao, Tianjun 
;Montes De Oca Roldan, Marco ;Stützle, Thomas
Référence Lecture notes in computer science, 7401 LNCS, page (85-96)
Publication Publié, 2012
;Montes De Oca Roldan, Marco ;Stützle, Thomas Référence Lecture notes in computer science, 7401 LNCS, page (85-96)
Publication Publié, 2012
Article révisé par les pairs
| Résumé : | We modify an artificial bee colony algorithm as follows: we make the population size grow over time and apply local search on strategically selected solutions. The modified algorithm obtains very good results on a set of large-scale continuous optimization benchmark problems. This is not the first time we see that the two aforementioned modifications make an initially non-competitive algorithm obtain state-of-the-art results. In previous work, we have shown that the same modifications substantially improve the performance of particle swarm optimization and ant colony optimization algorithms. Altogether, these results suggest that population growth coupled with local search help obtain high-quality results. © 2012 Springer-Verlag. |
