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Nature Inspires New Algorithms

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Metaheuristics

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Abstract

Nature modeling is a leading trend in optimization methods. While genetic algorithms, ant-based methods, and particle swarm optimization are well-known examples, there is a continuous emergence of new algorithms inspired by nature. In this chapter, we give a short overview of the most recent promising new algorithms.

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Notes

  1. 1.

    Alternative link: https://sites.google.com/a/hydroteq.com/www/.

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  1. Laboratoire Informatique (EA6300), Université François Rabelais Tours, 64 Avenue Jean Portalis, 37200, Tours, France

    Sébastien Aupetit & Mohamed Slimane

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  1. Sébastien Aupetit
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Correspondence to Sébastien Aupetit .

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  1. Laboratory LiSSi (EA 3956), Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

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Aupetit, S., Slimane, M. (2016). Nature Inspires New Algorithms. In: Siarry, P. (eds) Metaheuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-45403-0_10

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