Linkage identification for real-valued loci by fitness difference classification
Linkage identification for real-valued loci by fitness difference classification
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DOI：
10.1109/cec.2005.1554843
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发表时间：
2005-12
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通讯作者：
Miwako Tsuji;M. Munetomo;K. Akama
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作者：
Miwako Tsuji;M. Munetomo;K. Akama
为了提高遗传算法的效率，重要的是要确定一个连锁集，即一组紧密连锁的基因座，以构建一个积木。在本文中，我们提出了一种新的连接识别方法的实值字符串称为实值依赖检测的分布来自df（rD/sup 5/）。它可以检测连锁集与拟线性适应度评价。rD/sup 5/是在针对二进制字符串提出的D/sup 5/的基础上设计的。它通过估计根据适应度差异分类的字符串的分布来检测位点的依赖性。rD/sup 5/和LINC-R（它是在别处提出的连锁识别方法之一）提供关于待求解的函数的近似等价信息，然而，对于较大的函数，rD/sup 5/执行比LINC-R更少的适应度评估。尽管分布估计算法（EDA）也估计字符串的分布，但EDA很难求解由指数缩放子函数组成的函数。相比之下，所提出的方法，可以适用于函数以类似的方式作为一个函数组成的均匀缩放的子函数，这是很容易的EDA。我们进行实验，比较所提出的方法与LINC-R，并检查rD/sup 5/的标度效应的稳定性。我们还调查了两个参数，定义的扰动（突变）的量，并定义的量化水平。
In order to enhance efficiency of genetic algorithms, it is important to identify a linkage set, i.e. a set of loci tightly linked to construct a building block. In this paper, we propose a novel linkage identification method for real-valued strings called the real-valued dependency detection for distribution derived from df (rD/sup 5/). It can detect linkage sets with quasilinear fitness evaluations. The rD/sup 5/ is designed based on the D/sup 5/ which has been proposed for binary strings. It detects dependencies of loci by estimating the distribution of strings classified according to fitness differences. The rD/sup 5/ and the LINC-R which is one of linkage identification methods proposed elsewhere, provide approximate equivalent information about a function to be solved, however, the rD/sup 5/ performs smaller number of fitness evaluations than the LINC-R for larger functions. Although estimation of distribution algorithms (EDAs) also estimate distribution of strings, it is difficult for EDAs to solve a function composed of exponentially scaled subfunctions. The proposed method, by contrast, can be applied to the function in the similar way to as to a function composed of uniformly scaled subfunctions which is easy for EDAs. We perform experiments to compare the proposed method with the LINC-R and to examine the scaling effect stability of the rD/sup 5/. We also investigate two parameters, that define the amount of perturbation (mutation) and that define the quantization level.