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Dynamic Graph Drawing with a Hybridized Genetic Algorithm

机译:具有杂交的遗传算法的动态图形图

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Automatic graph drawing algorithms, especially those for hierarchical digraphs, have an important place in computer-aided design software or more generally in software programs where an efficient visualization tool for complex structure is required. In these cases, aesthetics plays a major role for generating readable and understandable layouts. Besides, in an interactive approach, the program must preserve the mental map of the user between time t-1 and t. In this paper we introduce a dynamic drawing procedure for hierarchical digraph drawing. It tends to minimize arc-crossing thanks to a hybridized genetic algorithm. The hybridization consists of a local optimization step based on averaging heuristics and two problem-based crossover operators. A stability constraint based on a similarity measure is used to preserve the likeness between the layouts at time t-1 and t. Computational experiments have been done with an adapted random graph generator to simulate the construction process of 90 graphs. They con-rm tat, because of the actual algorithm, the arc crossing number of the selected layout is close to the best layout found. We show that computation of the similarity measure tends to preserve the likeness between the two layouts.
机译:自动图绘图算法,尤其是分层数字的绘图算法,在计算机辅助设计软件中具有重要位置,或者更普遍在软件程序中,需要有效的复杂结构的可视化工具。在这些情况下,美学对生成可读性和可理解的布局发挥着重要作用。此外,在互动方法中,该程序必须在时间t-1和t之间保留用户的心理映射。在本文中,我们引入了一个动态绘图程序,用于分层数字图。由于杂交的遗传算法,它倾向于最小化弧线。杂交包括基于平均启发式的局部优化步骤和基于两个问题的交叉运算符。基于相似度测量的稳定约束用于在时间T-1和T处保持布局之间的相似性。使用适应的随机图生成器进行了计算实验,以模拟90图的施工过程。它们Con-RM TAT,由于实际算法,所选布局的弧线交叉数量接近找到的最佳布局。我们表明,相似度测量的计算倾向于保持两个布局之间的相似性。

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