International Journal of Computational Intelligence Systems

Volume 9, Issue 4, August 2016, Pages 778 - 787

A hybrid gene expression programming algorithm based on orthogonal design

Authors
Jie Yangjiey@uow.edu.au, Jun Majma@uow.edu.au
SMART Infrastructure Facility, Faculty of Engineering and Information Sciences, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
Received 26 November 2015, Accepted 11 April 2016, Available Online 1 August 2016.
DOI
10.1080/18756891.2016.1204124How to use a DOI?
Keywords
Evolutionary computation; Gene expression programming; Orthogonal design; Evolutionary stable strategy
Abstract

The last decade has witnessed a great interest on the application of evolutionary algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO) and gene expression programming (GEP), for optimization problems. This paper presents a hybrid algorithm by combining the GEP algorithm and the orthogonal design method. A multiple-parent crossover operator is introduced for the chromosome reproduction using the orthogonal design method. In addition, an evolutionary stable strategy is also employed to maintain the population diversity during the evolution. The efficiency of the proposed algorithm is evaluated using three benchmark problems. The results demonstrate that the proposed hybrid algorithm has a better generalization ability compared to conventional algorithms.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 4
Pages
778 - 787
Publication Date
2016/08/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1204124How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Jie Yang
AU  - Jun Ma
PY  - 2016
DA  - 2016/08/01
TI  - A hybrid gene expression programming algorithm based on orthogonal design
JO  - International Journal of Computational Intelligence Systems
SP  - 778
EP  - 787
VL  - 9
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1204124
DO  - 10.1080/18756891.2016.1204124
ID  - Yang2016
ER  -