A Ranking-Based Firefly Algorithm with Adaptive Parameter Control and Modified Attraction
Wangping Xiong, Qinqin Wu, Peng Liu, Zhaoxing Xu · International Journal of Bio-Inspired Computation · 2024
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.