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Parametrization and Balancing Local and Global Search

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Handbook of Memetic Algorithms

Part of the book series: Studies in Computational Intelligence ((SCI,volume 379))

Introduction

This chapter is devoted to the parametrization of memetic algorithms and how to find a good balance between global and local search. This is one of the most pressing questions when designing a hybrid algorithm. The idea of hybridization is to combine the advantages of different components. But if one components dominates another one, hybridization may become more hindering than useful and computational effort may be wasted. For the case of memetic algorithms, if the effect of local search is too strong, the algorithm may quickly get stuck in local optima of bad quality.Moreover, the algorithm is likely to rediscover the same local optimum over and over again. Lastly, an excessive local search quickly leads to a loss of diversity within the population.

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© 2012 Springer-Verlag Berlin Heidelberg

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Sudholt, D. (2012). Parametrization and Balancing Local and Global Search. In: Neri, F., Cotta, C., Moscato, P. (eds) Handbook of Memetic Algorithms. Studies in Computational Intelligence, vol 379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23247-3_5

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  • DOI: https://doi.org/10.1007/978-3-642-23247-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23246-6

  • Online ISBN: 978-3-642-23247-3

  • eBook Packages: EngineeringEngineering (R0)

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