Bat algorithm

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]

The idealization of echolocation can be summarized as follows: Each virtual bat fly randomly with a velocity $v_{i}$ at position (solution) $x_{i}$ with a varying frequency or wavelength and loudness $A_{i}$ . As it searches and finds its prey, it changes frequency, loudness and pulse emission rate $r$ . Search is intensified by a local random walk. Selection of the best continues until certain stop criteria are met.

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)

[1] 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

[2] Altringham, J. D., Bats: Biology and Behaviour, Oxford Univesity Press, (1996).

[3] Richardson, P., Bats. Natural History Museum, London, (2008)

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