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A hybrid gene expression programming algorithm based on orthogonal design

Journal Article


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.

Publication Date


  • 2016

Citation


  • Yang, J. & Ma, J. (2016). A hybrid gene expression programming algorithm based on orthogonal design. International Journal of Computational Intelligence Systems, 9 (4), 778-787.

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5705

Number Of Pages


  • 9

Start Page


  • 778

End Page


  • 787

Volume


  • 9

Issue


  • 4

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.

Publication Date


  • 2016

Citation


  • Yang, J. & Ma, J. (2016). A hybrid gene expression programming algorithm based on orthogonal design. International Journal of Computational Intelligence Systems, 9 (4), 778-787.

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5705

Number Of Pages


  • 9

Start Page


  • 778

End Page


  • 787

Volume


  • 9

Issue


  • 4