An Extension of Gene Expression Programming with Hybrid Selection

被引：4
作者：
Liu, Julie Yu-Chih [1 ]
Chen, Jeng-Her Alex [1 ]
Chiu, Chiang-Tien [1 ]
Hsieh, Juo-Chiang [1 ]
机构：
[1] Yuan Ze Univ, Dept Informat Management, Tau Yuan 32003, Taiwan
来源：
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNOLOGIES AND ENGINEERING SYSTEMS (ICITES2013) | 2014年 / 293卷
关键词：
Evolutionary algorithm; Gene expression programming; Hybrid selection; Local optimum;
D O I：
10.1007/978-3-319-04573-3_79
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Premature convergence and suboptimal solutions are inevitable problems for evolutionary algorithms, such as Gene Expression Programming (GEP). This study proposes an extension of GEP which includes a hybrid selection method and a diversity maintenance mechanism to release local optimum of the GEP algorithm. The hybrid selection involves the Clonal selection and the Roulette wheel method. The experimental results show that the proposed algorithm outperforms Ferreira's GEP algorithm.
引用
收藏
页码：635 / 641
页数：7
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