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Title: Gaussian bare-bones firefly algorithm

Authors: Hu Peng; Shunxu Peng

Addresses: School of Information Science and Technology, Jiujiang University, Jiujiang, China ' Library, Jiujiang University, Jiujiang, China

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.

Keywords: firefly algorithm; swarm intelligence; Gaussian bare-bones; global optimisation.

DOI: 10.1504/IJICA.2019.100535

International Journal of Innovative Computing and Applications, 2019 Vol.10 No.1, pp.35 - 42

Received: 24 Jul 2018
Accepted: 23 Nov 2018

Published online: 28 Jun 2019 *

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