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arXiv 2303.05136cs.CG
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一种用于直线交叉最小化的新启发式算法

A New Heuristic for Rectilinear Crossing Minimization

François Doré, Enrico Formenti

AI总结:

本文提出一种基于射线投射和迭代重定位的直线交叉最小化启发式算法,其性能可与 OGDF 等经典图绘制库中的最佳方法相媲美。

摘要:

本文提出了一种用于直线交叉最小化的新启发式算法。该方法基于在初始图绘制之后迭代重新定位节点的思想。节点的新位置通过从该节点向图的边投射射线来计算。每条射线获得一个评分,评分最优的射线决定新位置。与经典图绘制库(如 OGDF)中可找到的最佳竞争方法相比,该启发式算法表现出令人关注的性能。

英文摘要:

A new heuristic for rectilinear crossing minimization is proposed. It is based on the idea of iteratively repositioning nodes after a first initial graph drawing. The new position of a node is computed by casting rays from the node towards graph edges. Each ray receives a mark and the one with the best mark determines the new position. The heuristic has interesting performances when compared to the best competitors which can be found in classical graph drawing libraries like OGDF.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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