A New Mutation Operator Based on the T Probability Distribution in Evolutionary Programming

Author

Gong, Wenyin ; Cai, Zhihua ; Lu, Xinwei ; Jiang, Siwei

Author_Institution

Sch. of Comput. Sci., China Univ. of Geosciences, Wuhan

Volume

2

fYear

2006

fDate

17-19 July 2006

Firstpage

675

Lastpage

679

Abstract

A new mutation operator based on the T probability distribution is studied. The T probability distribution is stable and can generate an offspring that is farther away from its parent than the commonly employed Gaussian mutation. Moreover, it has a better fine-tuning ability than the Cauchy mutation. In this paper, evolutionary programming (EP) with mutations based on the T probability distribution is studied. The new algorithm is tested on 23 benchmark functions and compared with the conventional EP and the fast EP. The experimental results demonstrate that the performance of the proposed algorithm outperforms the conventional EP and the fast EP

Keywords

evolutionary computation; mathematical operators; statistical distributions; evolutionary programming; fine-tuning ability; function optimization; mutation operator; probability distribution; Benchmark testing; Distributed computing; Functional programming; Game theory; Gaussian distribution; Genetic mutations; Genetic programming; Geology; Helium; Probability distribution; Evolutionary programming; T mutation; T probability distribution; function optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

1-4244-0475-4

Type

conf

DOI

10.1109/COGINF.2006.365569

Filename

4216487