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Swarm Intelligence

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Abstract

Nature-inspired optimization algorithms can, generally, be grouped into evolutionary approaches and swarm intelligence methods. EAs try to improve the candidate solutions (chromosomes) using evolutionary operators. Swarm intelligence methods use differential position update rules for obtaining new candidate solutions. The popularity of the swarm intelligence methods is due to their simplicity, easy adaptation to the problem, and effectiveness in solving the complex optimization problems.

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  1. Xonlink Inc, Ningbo, Zhejiang, China

    Ke-Lin Du

  2. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

    Ke-Lin Du & M. N. S. Swamy

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  1. Ke-Lin Du
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  2. M. N. S. Swamy
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Du, KL., Swamy, M.N.S. (2016). Swarm Intelligence. In: Search and Optimization by Metaheuristics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-41192-7_15

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