Use of the q-Gaussian mutation in evolutionary algorithms.

Date

2011

Advisors

Journal Title

Journal ISSN

ISSN

1432-7643

Volume Title

Publisher

Springer-Verlag.

Type

Article

Peer reviewed

Yes

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

Keywords

Evolutionary algorithms, q-Gaussian distribution, Self-adaptation, Evolutionary programming, Mutation distribution

Citation

Tinos, R and Yang, S. (2011) Use of the q-Gaussian mutation in evolutionary algorithms. Soft Computing, 15(8), August 2011, pp. 1523-1549.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)