Fireworks algorithm for optimization

Authors:
Ying Tan;Yuanchun Zhu
Affiliations:
Key Laboratory of Machine Perception (MOE), Peking University Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing, China;Key Laboratory of Machine Perception (MOE), Peking University Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing, China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Abstract

Inspired by observing fireworks explosion, a novel swarm intelligence 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 demonstrate the validation of the FA, a number of experiments were conducted on nine benchmark test functions to compare the FA with two variants 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.