Bat-inspired algorithm is a metaheuristic search optimization developed by Xin-She Yang in 2010.[1] This bat algorithm is based on the echolocation behaviour of microbats with varying pulse emission and loudness.[2][3]
Algorithm Description
The idealization of echolocation can be summarized as follows: Each virtual bat fly randomly with a velocity at position (solution) with a varying frequency or wavelength and loudness . As it searches and finds its prey, it changes frequency, loudness and pulse emission rate . Search is intensified by a local random walk. Selection of the best continues until certain stop criteria are met.
A detailed intrudction of metaheuristic algorithms including bat algorithms is given by Yang [4] where a demo program in Matlab/Octave is available, while a comprehensive review is carried out by Parpinelli and Lopes.Cite error: A <ref> tag is missing the closing </ref> (see the help page).
References
- ^ Yang, X.-S., A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65-74 (2010). http://arxiv.org/abs/1004.4170
- ^ Altringham, J. D., Bats: Biology and Behaviour, Oxford Univesity Press, (1996).
- ^ Richardson, P., Bats. Natural History Museum, London, (2008)
- ^ Yang, X. S., Nature-Inspired Metaheuristic Algoirthms, 2nd Edition, Luniver Press, (2010).