Summary
Proceedings of the 2013 International Symposium on Nonlinear Theory and its Applications
2013
Session Number:B3L-B
Session:
Number:310
Network-Structured Firefly Algorithm and its Behavior
Haruna Matsushita, Daiki Matsumoto, Yoshifumi Nishio,
pp.310-313
Publication Date:
Online ISSN:2188-5079
Summary:
This paper proposes a network-structured firefly algorithm (NS-FA). The standard firefly algorithm (FA) consists of multiple fireflies. An attractiveness of the firefly is proportional to its brightness, and for any two fireflies, the less brighter one will be attracted by the brighter one at every generation step. However, the fireflies of the NS-FA have a network structure that changes with generation step, and they move depending on its network structure. That is to say, the firefly of the NS-FA is not affected by brighter firefly if there is no connection between the two fireflies. In other words, even if there is brighter firefly in the firefly swarm, the firefly is not always attracted to the brighter firefly. We apply the NS-FA to various optimization benchmarks and confirm its effectiveness.
References:
[1] J. Kennedy and R. C. Eberhart, “Particle swarm optimization,” in Proc. of IEEE. Int. Conf. on Neural Netw., pp. 1942-1948, 1995.
[2] Yang. X. S., “Nature-Inspired Metaheuristic Algorithms”, Luniver Press, 2008.