Introduction to Fireworks Algorithm

Ying Tan, Chao Yu, Shaoqiu Zheng and Ke Ding
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Ying Tan: School of Electronics Engineering and Computer Science, Peking University, Beijing, China
Chao Yu: School of Electronics Engineering and Computer Science, Peking University, Beijing, China
Shaoqiu Zheng: School of Electronics Engineering and Computer Science, Peking University, Beijing, China
Ke Ding: School of Electronics Engineering and Computer Science, Peking University, Beijing, China

International Journal of Swarm Intelligence Research (IJSIR), 2013, vol. 4, issue 4, 39-70

Abstract: Inspired by fireworks explosion at night, conventional fireworks algorithm (FWA) was developed in 2010. Since then, several improvements and applications were proposed to improve the efficiency of FWA. In this paper, the conventional fireworks algorithm is first summarized and three improved fireworks algorithms are provided. By changing the ways of calculating the numbers and amplitudes of sparks in fireworks' explosion, the improved FWA algorithms become more reasonable and explainable. In addition, the multi-objective fireworks algorithm and the graphic processing unit (GPU) based fireworks algorithm are also presented, particularly the GPU based fireworks algorithm is able to speed up the optimization process considerably. Extensive experiments on 13 benchmark functions demonstrate that the three improved fireworks algorithms significantly increase the accuracy of found solutions, yet decrease the running time dramatically. At last, some applications of fireworks algorithm are briefly described, while its shortcomings and future research directions are identified.

Date: 2013
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