Improving firefly algorithm using hybrid strategies Online publication date: Mon, 14-May-2018
by Gan Yu; Yingying Feng
International Journal of Computing Science and Mathematics (IJCSM), Vol. 9, No. 2, 2018
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).
Online publication date: Mon, 14-May-2018
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