Title: Firefly algorithm with generalised opposition-based learning

Authors: Hui Wang; Wenjun Wang; Hui Sun

Addresses: School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang 330099, China ' School of Business Administration, Nanchang Institute of Technology, Nanchang 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China; Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang 330099, China

Abstract: Firefly Algorithm (FA) is a new optimisation algorithm based on swarm intelligence, which has shown good performance on many optimisation problems. However, the standard FA easily falls into local minima because of too many attraction operations. To enhance the performance of the standard FA, a new FA is proposed in this paper. The new approach employs Generalised Opposition-Based Learning (GOBL) for population initialisation and generation jumping. To verify the performance of our approach, a set of benchmark functions tested in the experiments. Computational results show that the proposed approach obtains better performance than the standard FA and some recently proposed FA variants.

Keywords: firefly algorithm; generalised opposition-based learning; GOBL; global optimisation; numerical optimisation; population initialisation; generation jumping.

DOI: 10.1504/IJWMC.2015.074028

International Journal of Wireless and Mobile Computing, 2015 Vol.9 No.4, pp.370 - 376

Received: 30 May 2015
Accepted: 09 Jun 2015
Published online: 03 Jan 2016 *

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