New crossover operator based on semantic distance between subtrees in Genetic Programming
New crossover operator based on semantic distance between subtrees in Genetic Programming
复制标题
遗传规划中基于子树语义距离的新型交叉算子
DOI：
10.1109/icsmc.2012.6377812
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
T. Takahama
中科院分区：
文献类型：
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作者：
Akira Hara;Yoshimasa Ueno;T. Takahama
遗传编程(GP)是一种生成树结构程序的进化方法。遗传算法中的正常子树交叉随机地在每棵父树中选择一个交叉点，通过交换所选择的子树来产生后代。在常规交叉算法中，由于没有考虑子树之间的相似性，使得全局搜索和局部搜索难以控制。本文提出了一种新的基于子树间语义距离的交叉操作。我们称这种操作为语义控制交叉。通过使用语义控制交叉，可以在搜索的早期阶段执行全局搜索，并随着搜索的进行将搜索性质转移到局部搜索。实验结果表明，语义控制交叉比传统交叉具有更好的性能。
Genetic Programming (GP) is an evolutionary method for generating tree structural programs. Normal subtree crossover in GP randomly selects a crossover point in each parental tree, and offspring are created by exchanging the selected subtrees. In the normal crossover, it is difficult to control the global and local search because the similarity between the subtrees is not considered. In this paper, we propose a new crossover operation based on the semantic distance between the subtrees. We call this operation Semantic Control Crossover. By using the Semantic Control Crossover, the global search can be performed in the early stage of search, and the search property can be shifted to the local search as the search proceeds. As the results of experiments, the Semantic Control Crossover showed better performance than the conventional crossover.
DOI：
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发表时间：
1992
期刊：
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影响因子：
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作者：
J. Koza
通讯作者：
J. Koza