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Introduction to Fireworks Algorithm

Ying Tan, Chao Yu, Shaoqiu Zheng, Ke Ding

Source Title: International Journal of Swarm Intelligence Research (IJSIR)4(4)

ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781466635272|DOI: 10.4018/ijsir.2013100103

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MLA

Tan, Ying, et al. "Introduction to Fireworks Algorithm." IJSIR vol.4, no.4 2013: pp.39-70. http://doi.org/10.4018/ijsir.2013100103

APA

Tan, Y., Yu, C., Zheng, S., & Ding, K. (2013). Introduction to Fireworks Algorithm. International Journal of Swarm Intelligence Research (IJSIR), 4(4), 39-70. http://doi.org/10.4018/ijsir.2013100103

Chicago

Tan, Ying, et al. "Introduction to Fireworks Algorithm," International Journal of Swarm Intelligence Research (IJSIR) 4, no.4: 39-70. http://doi.org/10.4018/ijsir.2013100103

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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.

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Introduction to Fireworks Algorithm

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