Rank-based Semantic Control Crossover in Genetic Programming
Rank-based Semantic Control Crossover in Genetic Programming
复制标题
遗传编程中基于排序的语义控制交叉
DOI：
10.1109/smc.2014.6973957
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
T. Takahama
中科院分区：
文献类型：
--
作者：
Akira Hara;J. Kushida;Takeyuki Nobuta;T. Takahama
遗传程序设计（GP）中常用的子树交换交叉算法，由于父代个体中交叉点的随机选择，无法控制全局或局部搜索等搜索特性。为了克服这一问题，近年来人们研究了基于子树语义距离的交叉算法。如果语义空间中的相似子树被交换，则可以执行局部搜索。相反，交换不同的子树，可以执行全局搜索。在语义控制交叉（SCC）中，全局搜索可以在早期代中执行，局部搜索可以在后期代中执行。在本文中，我们提出了一种新的SCC的基础上的排名信息的父母，排名为基础的SCC。该方法不是根据代数而是根据父代的排序信息来控制搜索属性。在交叉到具有较高秩的一对父树的情况下，相似的子树应该被交换用于围绕父树的局部搜索。相反，在交叉到具有较低秩的一对父树的情况下，应该交换不相似的子树以进行全局搜索。比较了标准交叉、传统SCC和基于秩的SCC三种方法的搜索性能，证明了本文方法的有效性。
Subtree exchange crossover which is usually used in Genetic Programming (GP) can not control the search properties such as global or local search, because crossover points in parental individuals are selected at random. To overcome the problem, crossover based on semantic distance of subtrees has been studied recent years. If similar subtrees in semantic space are exchanged, the local search can be performed. In contrast, dissimilar subtrees are exchanged, the global search can be performed. In Semantic Control Crossover (SCC), the global search can be performed in early generations, and the local search can be performed in later generations. In this paper, we propose a new SCC based on the ranking information of parents, Rank-based SCC. The method controls search properties according to not generations but ranking information of parents. In case of the crossover to a pair of parents with higher ranks, similar subtrees should be exchanged for local search around the parents. In contrast, in case of the crossover to a pair of parents with lower ranks, dissimilar subtrees should be exchanged for global search. We compared the search performance of three methods, standard crossover, conventional SCC and Rank-based SCC, and showed the effectiveness of our method.
DOI：
--
发表时间：
1992
期刊：
--
影响因子：
--
作者：
J. Koza
通讯作者：
J. Koza