article · International Journal of Innovative Computing and Applications · 2019
Gaussian bare-bones firefly algorithm
Cited by 9Abstract and details only
Abstract
Firefly algorithm (FA), as a relatively recent emerged swarm intelligence algorithm, is powerful and popular for the complex real parameter global optimisation. However, the premature convergence has greatly affected the performance of original FA. To overcome this problem, we proposed a Gaussian bare-bones FA, named GBFA, in which each firefly moves to a Gaussian bare-bones method generated learning object rather than its better neighbours. The experiments are conducted on a set of widely used benchmark functions. Experimental results and comparison with the state-of-the-art FA variants have proved that the proposed algorithm is promising.
Cite this paper
Peng, H., & Peng, S. (2019). Gaussian bare-bones firefly algorithm. International Journal of Innovative Computing and Applications, 10(1), 35. https://doi.org/10.1504/ijica.2019.100535
Peng, Hu, and Shunxu Peng. “Gaussian bare-bones firefly algorithm.” International Journal of Innovative Computing and Applications, vol. 10, no. 1, 2019, p. 35, https://doi.org/10.1504/ijica.2019.100535.
Peng, Hu, and Shunxu Peng. 2019. “Gaussian bare-bones firefly algorithm.” International Journal of Innovative Computing and Applications 10 (1): 35. https://doi.org/10.1504/ijica.2019.100535.
Peng, H. and Peng, S. (2019) ‘Gaussian bare-bones firefly algorithm’, International Journal of Innovative Computing and Applications, 10(1), p. 35. Available at: https://doi.org/10.1504/ijica.2019.100535.
@article{peng2019gaussian,
title = {{Gaussian bare-bones firefly algorithm}},
author = {Peng, Hu and Peng, Shunxu},
journal = {International Journal of Innovative Computing and Applications},
volume = {10},
number = {1},
pages = {35},
year = {2019},
doi = {10.1504/ijica.2019.100535}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.