Title: Improving firefly algorithm using hybrid strategies

Authors: Gan Yu; Yingying Feng

Addresses: School of Information Engineering, Fuyang Normal University, Fuyang 236037, China ' School of Information Engineering, Fuyang Normal University, Fuyang 236037, China

Abstract: In this paper, we present a new firefly algorithm (FA) by using hybrid strategies to obtain a good optimisation performance. The proposed approach, namely HFA, employs three strategies. First, an adaptive parameter method is utilised to dynamically changing the step factor. Second, HFA uses a modified search strategy and eliminates the concept of attractiveness. So, HFA does not include two parameters, absorption coefficient and initial attractiveness. Third, a probabilistic attraction model is used to replace the original full attraction model. Experiments on some benchmark problems show that HFA is superior to mimetic FA (MFA) and probabilistic attraction-based FA (PAFA).

Keywords: firefly algorithm; adaptive parameter; probabilistic attraction; optimisation.

DOI: 10.1504/IJCSM.2018.091749

International Journal of Computing Science and Mathematics, 2018 Vol.9 No.2, pp.163 - 170

Received: 29 Nov 2017
Accepted: 02 Jan 2018

Published online: 30 Apr 2018 *

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