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Title: Use of the q-Gaussian mutation in evolutionary algorithms
Authors: Tinós, R
Yang, S
Keywords: Evolutionary algorithms;q-Gaussian distribution;Self-adaptation;Evolutionary programming;Mutation distribution
Issue Date: 2011
Publisher: Springer
Citation: Soft Computing, 15(8): 1523 - 1549, Aug 2011
Abstract: This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.
Description: Copyright @ Springer-Verlag 2010.
ISSN: 1432-7643
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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