Colorful path detection in vertex-colored temporal

IF 1.4 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY
R. Dondi, M. Hosseinzadeh
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引用次数: 0

Abstract

Finding paths is a fundamental problem in graph theory and algorithm design due to its many applications. Recently, this problem has been considered on temporal graphs, where edges may change over a discrete time domain. The analysis of graphs has also taken into account the relevance of vertex properties, modeled by assigning to vertices labels or colors. In this work, we deal with a problem that, given a static or temporal graph, whose vertices are colored graph looks for a path such that (1) the vertices of the path have distinct colors and (2) that path includes the maximum number of colors. We analyze the approximation complexity of the problem on static and temporal graphs, and we prove an inapproximability bound. Then, we consider the problem on temporal graphs, and we design a heuristic for it. We present an experimental evaluation of our heuristic, both on synthetic and real-world graphs. The experimental results show that for many instances of the problem, our method is able to return near-optimal solutions.
彩色路径检测在顶点彩色时间
路径查找是图论和算法设计中的一个基本问题,因为它有很多应用。最近,在时间图上考虑了这个问题,其中边可能在离散时域上发生变化。图的分析还考虑了顶点属性的相关性,通过为顶点指定标签或颜色来建模。在这项工作中,我们处理了一个问题,即给定一个静态或时间图,其顶点是有色的。图寻找一条路径,使得(1)该路径的顶点具有不同的颜色,(2)该路径包括最大数量的颜色。我们分析了该问题在静态图和时间图上的近似复杂性,并证明了一个不可逼近界。然后,我们考虑了时间图上的问题,并为此设计了一个启发式算法。我们对我们的启发式算法进行了实验评估,包括在合成图和真实世界图上。实验结果表明,对于该问题的许多实例,我们的方法能够返回接近最优的解。
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来源期刊
Network Science
Network Science SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
3.50
自引率
5.90%
发文量
24
期刊介绍: Network Science is an important journal for an important discipline - one using the network paradigm, focusing on actors and relational linkages, to inform research, methodology, and applications from many fields across the natural, social, engineering and informational sciences. Given growing understanding of the interconnectedness and globalization of the world, network methods are an increasingly recognized way to research aspects of modern society along with the individuals, organizations, and other actors within it. The discipline is ready for a comprehensive journal, open to papers from all relevant areas. Network Science is a defining work, shaping this discipline. The journal welcomes contributions from researchers in all areas working on network theory, methods, and data.
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