Firefly Algorithm with Luciferase Inhibition Mechanism

Abstract

Firefly algorithm (FA) was proposed by Yang which inspired from communication between fireflies through flash. As an efficient swarm intelligence algorithm, FA has been successfully applied in real-world applications. However, FA employs full attraction model that the method of selecting fireflies is sequential selection, namely each firefly can be attracted to other all fireflies in the worst case. This causes FA is prone to fall into local optima and high computational complexity. Inspired by the principle of firefly glow, an enhanced FA variant is proposed, namely, firefly algorithm with luciferase inhibition mechanism (LiFA), where luciferase inhibition mechanism is introduced to improve the effectiveness of selection. Besides, adaptive attraction model is also proposed to reduce the computational complexity and balance exploration and exploitation. Experiments are conducted on CEC2013 test suite to verify the performance of LiFA. The results show that LiFA has the best performance in some complex functions when compared other advanced FA variants.