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Improving the Performance of the Fish School Search Algorithm

Improving the Performance of the Fish School Search Algorithm

Rodrigo P. Monteiro, Luiz F. V. Verçosa, Carmelo J. A. Bastos-Filho
Copyright: © 2018 |Volume: 9 |Issue: 4 |Pages: 26
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781522544876|DOI: 10.4018/IJSIR.2018100102
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MLA

Monteiro, Rodrigo P., et al. "Improving the Performance of the Fish School Search Algorithm." IJSIR vol.9, no.4 2018: pp.21-46. http://doi.org/10.4018/IJSIR.2018100102

APA

Monteiro, R. P., Verçosa, L. F., & Bastos-Filho, C. J. (2018). Improving the Performance of the Fish School Search Algorithm. International Journal of Swarm Intelligence Research (IJSIR), 9(4), 21-46. http://doi.org/10.4018/IJSIR.2018100102

Chicago

Monteiro, Rodrigo P., Luiz F. V. Verçosa, and Carmelo J. A. Bastos-Filho. "Improving the Performance of the Fish School Search Algorithm," International Journal of Swarm Intelligence Research (IJSIR) 9, no.4: 21-46. http://doi.org/10.4018/IJSIR.2018100102

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Abstract

In this article, the authors propose a new version of Fish School Search Algorithm named FSS-CS. This release has three significant changes. First, it has an improved feeding mechanism to enhance the barycenter calculation. Secondly, it promotes exploration by using a state-of-art, non-greedy strategy. Finally, it incorporates a promising existent elliptic step decay. The authors assessed the proposal in ten benchmark optimization problems to evaluate the performance. The results show that the proposed version outperformed in most cases the FSS versions for mono-modal optimization.

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