improved Firefly Algorithm (iFA)

The firefly algorithm [1, 2] is a nature-inspired, population-based metaheuristic algorithm that mimics the flashing and movement behavior of the fireflies. The brightness/attractiveness of the fireflies is a relative term. It depends on the distance between any two fireflies, shape and type of the landscape, and few environmental factors. In this improved version of the firefly algorithm, few rules have been proposed to keep a better balance between the exploration and exploitation capabilities of the algorithm.

iFA

Effects of some environmental factors (for example landscape structure, light intensity and density of the fog) in the visibility of the fireflies.

Article source

The original article has been published in Applied Soft Computing (Elsevier). Inspiration, mathematical model, competitiveness of the proposed algorithm with state-of-the-art metaheuristic optimization methods have been discussed here.

Source code

The source codes of the iFA are written in MATLAB R2014a.

References

  1. X.-S. Yang, Nature-Inspired Metaheuristic Algorithms, 2nd ed., Luniver Press, United Kingdom, 2010.
  2. X.-S. Yang, Firefly Algorithms for Multimodal Optimization, in: Stoch. Algorithms Found. Appl., Springer, Berlin, Heidelberg, 2009: pp. 169–178. https://doi.org/10.1007/978-3-642-04944-6_14.