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.
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: 14 May 2018 *