Modified Mutated Firefly Algorithm
Ariel O. Gamao, Bobby D. Gerardo, Ruji P. Medina · 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS) · 2019
The strength of the Firefly algorithm depends on the attractiveness of fireflies with lesser intensity towards the superior firefly with brighter intensity. The mutated firefly algorithm (MFA) explores the search space by enhancing the features of less glowing fireflies from more luminous fireflies. The MFA converges faster than the standard FA using the 40:40 formula. With this, only the top 40 percent and bottom 40 percent of the fireflies join in the mutation process. Consequently, there has to be an added sorting algorithm to achieve such a preferred method. However, the sorting algorithm entails processing time depending on its applied technique, size of data, and CPU. A Modified Mutated Firefly Algorithm (MMFA) was developed to optimize the convergence time, employing a stochastic approach with increased convergence time. The results of the simulations show a significant improvement in terms of convergence time.