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Memetic Evolutionary Algorithms

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Recent Advances in Memetic Algorithms

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 166))

1 Summary

Memetic Evolutionary Algorithms (MAs) are a class of stochastic heuristics for global optimization which combine the parallel global search nature of Evolutionary Algorithms with Local Search to improve individual solutions. These techniques are being applied to an increasing range of application domains with successful results, and the aim of this book is both to highlight some of these applications, and to shed light on some of the design issues and considerations necessary to a successful implementation. In this chapter we provide a background for the rest of the volume by introducing Evolutionary Algorithms (EAs) and Local Search. We then move on to describe the synergy that arises when these two are combined in Memetic Algorithms, and to discuss some of the most salient design issues for a successful implementation. We conclude by describing various other ways in which EAs and MAs can be hybridized with domain-specific knowledge and other search techniques.

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Author information

Authors and Affiliations

  1. Sandia National Laboratory, Albuquerque, New Mexico, USA

    W. E. Hart

  2. Automatic Scheduling, Optimisation and Planning Group, School of Computer Science and IT, University of Nottingham, UK

    N. Krasnogor

  3. Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, BS16 12QY, UK

    J. E. Smith

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  1. W. E. Hart
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  2. N. Krasnogor
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  3. J. E. Smith
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Editors and Affiliations

  1. Algorithms and Discrete Mathematics Department, Sandia National Laboratories, 87185-1110, Albuquerque, NM, USA

    William E. Hart

  2. Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Coldharbour Lande, BS16 1QY, Bristol, UK

    J. E. Smith

  3. Automatic Scheduling, Optimisation and Planning Group, School of Computer Science and IT, University of Nottingham, Jubilee Campus Wollaton Road, NG8 1BB, Nottingham, UK

    N. Krasnogor

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Hart, W.E., Krasnogor, N., Smith, J.E. (2005). Memetic Evolutionary Algorithms. In: Hart, W.E., Smith, J.E., Krasnogor, N. (eds) Recent Advances in Memetic Algorithms. Studies in Fuzziness and Soft Computing, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32363-5_1

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  • DOI: https://doi.org/10.1007/3-540-32363-5_1

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  • Online ISBN: 978-3-540-32363-1

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