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FIREFLY ALGORITHM

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- 1. 5. FIREFLY ALGORITHM OPTIMIZATION
- 2. • FA is one of the recent swarm intelligence methods developed by Yang in 2008 and is a kind of stochastic, nature-inspired, meta- heuristic algorithm that can be applied for solving the hardest optimization problems (also NP-hard problems). This algorithm belongs to stochastic algorithms. This means, it uses a kind of randomization by searching for a set of solutions. It is inspired by the flashing lights of fireflies in nature. Heuristic means ‘to find’ or ‘to discover solutions by trial and error’. There is no guarantee that the optimal solution will be found in a reasonable amount of time
- 3. In the firefly algorithm, concentrates on the generation of new solutions within a search space and thus, selects the best solution for survival. Search process depends on balancing between two major components: exploration and exploitation One of the three rules used to construct the algorithm is that all fireflies are unisex, which means any firefly can be attracted to any other brighter one. The second rule is that the brightness of a firefly is determined from the encoded objective function. The last rule is that attractiveness is directly proportional to brightness but decreases with distance, and a firefly will move towards the brighter one, and if there is no brighter one, it will move randomly.
- 4. • From elementary physics it is clear that the intensity of light is inversely proportional to the square of the distance r, from the source. Furthermore when light passes through a medium with light absorption coefficient of λ the light intensity, I varies with distance r
- 8. Firefly Algorithm Flowchart