A hybrid gene expression programming algorithm based on orthogonal design

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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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  -