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Investigation of Mutation Schemes in Real-Parameter Genetic Algorithms

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7677)

Abstract

In this paper, we investigate the effect of five different mutation schemes for real-parameter genetic algorithms (RGAs). Based on extensive simulation studies, it is observed that a mutation clock implementation is computationally quick and also efficient in finding a solution close to the optimum on four different problems used in this study. Moreover, parametric studies on the polynomial mutation operator identify a working range of values of these parameters. This study signifies that the long-suggested mutation clock operator should be considered as a valuable mutation operator for RGAs.

Keywords

  • Mutation Operator
  • Mutation Probability
  • Mutation Scheme
  • Population Member
  • Problem Scheme

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2012 Springer-Verlag Berlin Heidelberg

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Deb, D., Deb, K. (2012). Investigation of Mutation Schemes in Real-Parameter Genetic Algorithms. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_1

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  • DOI: https://doi.org/10.1007/978-3-642-35380-2_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35379-6

  • Online ISBN: 978-3-642-35380-2

  • eBook Packages: Computer ScienceComputer Science (R0)