Fireworks Algorithm for Optimization Fireworks Algorithm for Optimization

Abstract

Inspired by observing fireworks explosion, a novel swarm in-telligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks are also well designed. In order to demon-strate the validation of the FA, a number of experiments were conducted on nine benchmark test functions to compare the FA with two vari-ants of particle swarm optimization (PSO) algorithms, namely Standard PSO and Clonal PSO. It turns out from the results that the proposed FA clearly outperforms the two variants of the PSOs in both convergence speed and global solution accuracy.