Adaptive Multi-phenotype Based Gene Expression Programming Algorithm

LI Qu; CHENG Hongbing; YAO Min

doi:10.1049/cje.2016.08.041

Volume 25 Issue 5

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Article Navigation > Chinese Journal of Electronics > 2016 > 25(5): 807-816

LI Qu, CHENG Hongbing, YAO Min, “Adaptive Multi-phenotype Based Gene Expression Programming Algorithm,” Chinese Journal of Electronics, vol. 25, no. 5, pp. 807-816, 2016, doi: 10.1049/cje.2016.08.041

Citation:

LI Qu, CHENG Hongbing, YAO Min, “Adaptive Multi-phenotype Based Gene Expression Programming Algorithm,” Chinese Journal of Electronics, vol. 25, no. 5, pp. 807-816, 2016, doi: 10.1049/cje.2016.08.041

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Adaptive Multi-phenotype Based Gene Expression Programming Algorithm

doi: 10.1049/cje.2016.08.041

LI Qu^1,2,
CHENG Hongbing^{1,3
,},
YAO Min²

1.
School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China;
2.
College of Computer Science, Zhejiang University, Hangzhou 310007, China;
3.
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61402413, No.61340058), the Six Kinds Peak Talents Plan Project of Jiangsu Province (No.11-JY-009), and the Natural Science Foundation of Zhejiang Province (No.LY14F020019, No.LZ14F020001).

More Information

Corresponding author: CHENG Hongbing (corresponding author) was born in 1979, associate professor. He received the Ph.D. degree from Nanjing University of Posts & Telecommunications. His research interest includes crptography and information security, computer communications and networks, and cloud computing (Email:chenghb@zjut.edu.cn).
Received Date: 2014-12-17
Rev Recd Date: 2015-04-21
Publish Date: 2016-09-10

Abstract

Abstract

Expression theory is the mathematical foundation of evolutionary computation. In order to investigate the problems in Gene expression programming (GEP) expression theory, we clarified the difference between genotypic expression space and phenotypic expression space. We also presented phenotypic expression space definition and theory. Then we analyzed the reason of good and bad performance of different GEP algorithms based on expression space theory. We also proposed a new Adaptive multi-phenotype gene expression programming (AMGEP), in which the potential of genes is fully activated with gene combination. Experiments on benchmark problems showed that genotypic expression space and phenotypic expression space theory can explain the different performance of different algorithms and showed that AMGEP outperform other GEP algorithms in terms of search ability.
- Gene expression programming (GEP),
- Genotype,
- Phenotype,
- Population diversity

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References(28)

References

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