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Discrete Branch Length Representations for Genetic Algorithms in Phylogenetic Search

机译:系统发育搜索中遗传算法的离散分支长度表示

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Likelihood analysis for phylogenetics is a well suited domain for optimization by genetic algorithm. A major factor in the performance of genetic algorithms is representation and operators. In this paper we present promising preliminary results on using a discrete set of edge lengths in the phylogenetic trees. We find that discretizing the edge lengths changes the fundamental character of the search and can produce higher quality trees. Our results suggest a search that is more robust to traps in local optima and an opportunity to better control the balance between topology search and edge length search.
机译:系统发育学的可能性分析是一个非常适合通过遗传算法进行优化的领域。遗传算法性能的主要因素是表示和运算符。在本文中,我们提出了在系统发生树中使用一组不连续的边长的有希望的初步结果。我们发现离散化边长会改变搜索的基本特征,并且可以生成更高质量的树。我们的结果表明,对于局部最优陷阱而言,这种搜索更为稳健,并且有机会更好地控制拓扑搜索和边长搜索之间的平衡。

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