An Improved Firefly Algorithm for Optimization Problems

Optimization problem is one of the most difficult and challenging problems that has received considerable attention over the last decade. Researchers have been constantly investigating better ways to solve it. Recently, one optimization technique called firefly algorithm has gained the interest of many researchers. This algorithm is a type of swarm intelligence algorithm based on the reaction of a firefly to the light of other fireflies. In this paper, we propose an improvement on the original firefly algorithm. The proposed algorithm takes into account not only the firefly’s reaction to light but also the following contributing factors: firefly’s gene exchange, its pheromone, and the impact the wind has on pheromone dispersion. We tested our proposed algorithm against the traditional firefly algorithm and the original genetic algorithm with six standard benchmark functions and found that our algorithm is not only more effective but also faster than the other two algorithms.