A novel method for real parameter optimization based on Gene Expression Programming
A novel method for real parameter optimization based on Gene Expression Programming
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一种基于基因表达编程的实参数优化新方法
DOI：
10.1016/j.asoc.2008.09.007
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发表时间：
2009-03
期刊：
影响因子：
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通讯作者：
Zuo, Jie
中科院分区：
文献类型：
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作者：
Zhu, Jun;Liu, Yintian;Tang, Rong;Tang, Changjie;Xu, Kaikuo;Zuo, Jie
Gene Expression Programming (GEP) is a new technique of evolutionary algorithm that implements genome/phoneme representation in computing programs. Due to its power in global search, it is widely applied in symbolic regression. However, little work has been done to apply it to real parameter optimization yet. This paper proposes a real parameter optimization method named Uniform-Constants based GEP (UC-GEP). In UC-GEP, the constant domain directly participates in the evolution. Our research conducted extensive experiments over nine benchmark functions from the IEEE Congress on Evolutionary Computation 2005 and compared the results to three other algorithms namely Meta-Constants based GEP (MC-GEP), Meta-Uniform-Constants based GEP (MUC-GEP), and the Floating Point Genetic Algorithm (FP-GA). For simplicity, all GEP methods adopt a one-tier index gene structure. The results demonstrate the optimal performance of our UC-GEP in solving multimodal problems and show that at least one GEP method outperforms FP-GA on all test functions with higher computational complexity.
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DOI：
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发表时间：
1991
期刊：
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影响因子：
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作者：
C. Janikow;Z. Michalewicz
通讯作者：
C. Janikow;Z. Michalewicz
DOI：
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发表时间：
2001-02
期刊：
Complex Syst.
影响因子：
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作者：
Cândida Ferreira
通讯作者：
Cândida Ferreira
DOI：
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发表时间：
2005
期刊：
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影响因子：
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作者：
P. Suganthan;N. Hansen;Jing J. Liang;K. Deb;Ying-Ping Chen;A. Auger;Santosh Tiwari
通讯作者：
P. Suganthan;N. Hansen;Jing J. Liang;K. Deb;Ying-Ping Chen;A. Auger;Santosh Tiwari
DOI：
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发表时间：
1990
期刊：
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影响因子：
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作者：
L. Davis
通讯作者：
L. Davis
DOI：
10.1007/bfb0029726
发表时间：
1990-10
期刊：
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影响因子：
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作者：
D. Goldberg
通讯作者：
D. Goldberg