Gaussian bare-bones firefly algorithm Online publication date: Sat, 29-Jun-2019
by Hu Peng; Shunxu Peng
International Journal of Innovative Computing and Applications (IJICA), Vol. 10, No. 1, 2019
Abstract: Firefly algorithm (FA), as a relatively recent emerged swarm intelligence algorithm, is powerful and popular for the complex real parameter global optimisation. However, the premature convergence has greatly affected the performance of original FA. To overcome this problem, we proposed a Gaussian bare-bones FA, named GBFA, in which each firefly moves to a Gaussian bare-bones method generated learning object rather than its better neighbours. The experiments are conducted on a set of widely used benchmark functions. Experimental results and comparison with the state-of-the-art FA variants have proved that the proposed algorithm is promising.
Online publication date: Sat, 29-Jun-2019
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Innovative Computing and Applications (IJICA):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com