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Simple Linkage Identification Using Genetic Clustering

机译:使用遗传聚类的简单联动识别

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The paper proposes a simple linkage identification method for binary optimization problems. The method is basically equivalent to the genetic clustering method, called GC, inspired by the speciation due to segregation distortion genes that was previously proposed by us. A genetic algorithm using the method, called GAuGC, is also proposed. The GAuGC is applied to decomposable, nearly decomposable, and indecomposable problems. The results show that the GAuGC better solves problems with weak decomposability than the linkage tree genetic algorithm for comparison and also show that it cannot handle the deception well.
机译:本文提出了一种简单的联系识别方法,用于二进制优化问题。该方法基本上等同于称为GC的遗传聚类方法,其受到先前由我们先前提出的偏析变形基因的影响。还提出了一种遗传算法,称为GAUGC的方法。 GAUGC应用于可分解,几乎可分解的和不可分解的问题。结果表明,GAUGC更好地解决了分解性弱的问题,而不是链接树遗传算法进行比较,并且还表明它无法处理欺骗性。

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