Evolutionary programming using the mutations based on the Levy probability distribution

Research output: Contribution to journalArticle

Authors

Colleges, School and Institutes

Abstract

\This paper studies evolutionary programming with mutations based on the Levy probability distribution. The Levy probability distribution has an infinite second moment and is, therefore, more likely to generate an offspring that is farther away from its parent than the commonly employed Gaussian mutation. Such likelihood depends on a parameter alpha in the Levy distribution. We propose an evolutionary,programming algorithm using adaptive as well as nonadaptive Levy mutations. The proposed algorithm was applied to multivariate functional optimization. Empirical evidence shows that, in the case of functions having many local optima, the performance of the proposed algorithm was better than that of classical evolutionary programming using Gaussian mutation.

Details

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIEEE Transactions on Evolutionary Computation
Volume8
Issue number1
Publication statusPublished - 1 Jan 2004

Keywords

  • mean-square displacement, Levy mutation, evolutionary optimization, evolutionary programming, Levy probability distribution