Title: A ranking-based firefly algorithm with adaptive parameter control and modified attraction

Authors: Zhaoxing Xu; Peng Liu; Qinqin Wu; Wangping Xiong

Addresses: School Big Data, Jiangxi Institute of Fashion Technology, Nanchang 330201, China ' School Big Data, Jiangxi Institute of Fashion Technology, Nanchang 330201, China ' School Big Data, Jiangxi Institute of Fashion Technology, Nanchang 330201, China ' School of Computer, Jiangxi University of Chinese Medicine, Nanchang 330004, China

Abstract: In this paper, an improved firefly algorithm (FA) is proposed for numerical optimisation. The new approach, termed RBFA, employs three strategies. First, each firefly is assigned a probability based on a ranking method. The probability determines whether a firefly moves to a new position. Then, a novel parameter method is designed to dynamically adjust the step size. Furthermore, a modified attraction strategy is used to strengthen the search efficiency. To verify the performance of RBFA, a set of famous benchmark problems are tested. Computational results demonstrate the proposed RBFA can obtain better performance than several other FA variants.

Keywords: firefly algorithm; FA; ranking method; adaptive parameter; dynamical adjustment; modified attraction; numerical optimisation.

DOI: 10.1504/IJBIC.2025.146915

International Journal of Bio-Inspired Computation, 2025 Vol.25 No.4, pp.239 - 246

Received: 21 Sep 2024
Accepted: 23 Nov 2024
Published online: 26 Jun 2025 *

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