FLFBA

Versión 1.0.0 (3,55 KB) por Redouane Boudjemaa

Fractional Lèvy flight bat algorithm for global optimisation

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A well-known metaheuristic is the bat algorithm (BA), which consists of an iterative learning process inspired by bats echolocation behaviour in searching for prays. Basically, the BA uses a predefined number of bats that collectively move on the search space to find
the global optimum. This article proposes the fractional Lèvy flight bat algorithm (FLFBA), which is an improved version of the classical BA. In the FLFBA the velocity is updated through fractional calculus and a local search procedure that uses a random walk based on
Lèvy distribution. Such modifications enhance the ability of the algorithm to escape from local optimal values.

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Boudjemaa, Redouane, et al. “Fractional Lévy Flight Bat Algorithm for Global Optimisation.” International Journal of Bio-Inspired Computation, vol. 15, no. 2, Inderscience Publishers, 2020, p. 100, doi:10.1504/ijbic.2020.10028011.

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FLFBA.m

Versión	Publicado	Notas de la versión
1.0.0	5 abr 2020		Descargar

MLA	Boudjemaa, Redouane, et al. “Fractional Lévy Flight Bat Algorithm for Global Optimisation.” International Journal of Bio-Inspired Computation, vol. 15, no. 2, Inderscience Publishers, 2020, p. 100, doi:10.1504/ijbic.2020.10028011.
APA	Boudjemaa, R., Ouaar, F., & Oliva, D. (2020). Fractional Lévy flight bat algorithm for global optimisation. International Journal of Bio-Inspired Computation, 15(2), 100. Inderscience Publishers. Retrieved from https://doi.org/10.1504%2Fijbic.2020.10028011
BibTeX	@article{Boudjemaa_2020, doi = {10.1504/ijbic.2020.10028011}, url = {https://doi.org/10.1504%2Fijbic.2020.10028011}, year = 2020, publisher = {Inderscience Publishers}, volume = {15}, number = {2}, pages = {100}, author = {Redouane Boudjemaa and Fatima Ouaar and Diego Oliva}, title = {Fractional L{\'{e}}vy flight bat algorithm for global optimisation}, journal = {International Journal of Bio-Inspired Computation} }