Firefly algorithm: Difference between revisions

Revision as of 13:49, 9 March 2010

Revision as of 09:23, 26 March 2010

Line 39:

Recent studies shows that the [[firefly algorithm]] is very efficient<ref>X. S. Yang, Firefly algorithms for multimodal optimization, in: Stochastic Algorithms: Foundations and Applications, SAGA 2009, Lecture Notes in Computer Sciences, Vol. 5792, pp. 169-178 (2009). eprint at http://arxiv.org/abs/1003.1466 </ref>, and could outperform other metaheuristic algorithms including [[particle swarm optimization]].<ref>S. Lukasik and S. Zak, Firefly algorithm for continuous constrained optimization task, ICCCI 2009, Lecture Notes in Artificial Intelligence (Eds. N. T. Ngugen, R. Kowalczyk, S. M. Chen), Vol. 5796, 97-100 (2009).</ref>

Most metaheuristic algorithms may have difficulty in dealing with stochastic test functions, and it seems that firefly algorithm can deal with stochastic test functions<ref>Yang,X.-S., Firefly algorithm, stochastic test functions and design optimisation, Int. J. Bio-inspired Computation, Vol. 2, No. 2, pp. 78-84 (2010). eprint at http://arxiv.org/abs/1003.1409 </ref> very efficiently.

==See also==

* [[Metaheuristic]]

* [[Glowworm swarm optimization]] (GSO)

== References ==