Crazy Firefly Algorithm for Function Optimization

This paper present a new modification to firefly algorithm i.e crazy firefly algorithm by introducing a craziness operator to the existing algorithm to increase the diversity. The firefly algorithm is an algorithm of swarm intelligence that builds upon the reaction of firefly to illumination of other fireflies. It tests fine on innumerable statistical optimization complications. The algorithm in modified form utilizes the craziness factor to increase the diversity in searching conduct of standard algorithm. By testing the benchmark functions, the feasibility and efficacy of proposed algorithm are certified. Results demonstrate that the proposed algorithm gives superior performance in contrast to standard one when executed under a given set of control parameters. Other useful outcomes of crazy firefly are also tabulated which gives an thought that proposed modification algorithm refines standard firefly algorithm performance convergence further hurriedly to most select solution. more speedily with less time to generate finest solution.