Approximating the directed path partition problem

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Yong Chen , Zhi-Zhong Chen , Curtis Kennedy , Guohui Lin , Yao Xu , An Zhang
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引用次数: 0

Abstract

Given a digraph G=(V,E), the k-path partition problem aims to find a minimum collection of vertex-disjoint directed paths, of order at most k, to cover all the vertices. The problem has various applications. Its special case on undirected graphs is NP-hard when k3, and has received much study recently from the approximation algorithm perspective. However, the general problem on digraphs is seemingly untouched in the literature. We fill the gap with the first k/2-approximation algorithm, based on a novel concept of enlarging walk to minimize the number of singletons. Secondly, for k=3, we define a second novel kind of enlarging walks to greedily reduce the number of 2-paths in the 3-path partition and propose an improved 13/9-approximation algorithm. Lastly, for any k7, we present an improved (k+2)/3-approximation algorithm built on the maximum path-cycle cover followed by a careful 2-cycle elimination process.

近似有向路径分割问题
给定一个数图 G=(V,E),k 路径分割问题的目的是找到顶点相交的有向路径的最小集合,每条路径的阶数最多为 k,以覆盖 V 的所有顶点。该问题在设施定位、网络监控、交通网络等方面有多种应用。当 k≥3 时,它在无向图上的特例为 NP-hard,最近从近似算法的角度对其进行了大量研究。然而,关于数字图的一般问题,文献中似乎还没有涉及。我们填补了这一空白,提出了第一个 k/2 近似算法,对于任意 k≥3,该算法基于一个新颖的概念--扩大行走,以最小化 k 路径分区中的单子数。其次,对于 k=3,我们定义了第二种新的扩大行走,以贪婪地减少 3 路径分区中的 2 路径数量,并提出了一种改进的 13/9 近似算法。最后,对于任意 k≥7,我们提出了一种改进的 (k+2)/3 近似算法,该算法建立在最大路径循环覆盖上,然后是一个谨慎的 2 循环消除过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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