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Nature-Inspired Algorithms: Success and Challenges

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Engineering and Applied Sciences Optimization

Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 38))

Abstract

The simplicity and flexibility of nature-inspired algorithms have made them very popular in optimization and computational intelligence. Here, we will discuss the key features of nature-inspired metaheuristic algorithms by analyzing their diversity and adaptation, exploration and exploitation, attractions and diffusion mechanisms. We also highlight the success and challenges concerning swarm intelligence, parameter tuning and parameter control as well as some open problems.

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Author information

Authors and Affiliations

  1. School of Science and Technology, Middlesex University, London, NW4 4BT, UK

    Xin-She Yang

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  1. Xin-She Yang
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Correspondence to Xin-She Yang .

Editor information

Editors and Affiliations

  1. Institute of Structural Analysis & Seismic Research, National Technical University of Athens, Athens, Greece

    Nikos D. Lagaros

  2. Institute of Structural Analysis & Antiseismic Research, National Technical University of Athens, Athens, Greece

    Manolis Papadrakakis

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Yang, XS. (2015). Nature-Inspired Algorithms: Success and Challenges. In: Lagaros, N., Papadrakakis, M. (eds) Engineering and Applied Sciences Optimization. Computational Methods in Applied Sciences, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-319-18320-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-18320-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18319-0

  • Online ISBN: 978-3-319-18320-6

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