Better Hardness Results for the Minimum Spanning Tree Congestion Problem

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Algorithmica Pub Date : 2024-10-26 DOI:10.1007/s00453-024-01278-5
Huong Luu, Marek Chrobak
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引用次数: 0

Abstract

In the spanning tree congestion problem, given a connected graph G, the objective is to compute a spanning tree T in G that minimizes its maximum edge congestion, where the congestion of an edge e of T is the number of edges in G for which the unique path in T between their endpoints traverses e. The problem is known to be \(\mathbb{N}\mathbb{P}\)-hard, but its approximability is still poorly understood, and it is not even known whether the optimum solution can be efficiently approximated with ratio o(n). In the decision version of this problem, denoted \({\varvec{K}-\textsf {STC}}\), we need to determine if G has a spanning tree with congestion at most K. It is known that \({\varvec{K}-\textsf {STC}}\) is \(\mathbb{N}\mathbb{P}\)-complete for \(K\ge 8\), and this implies a lower bound of 1.125 on the approximation ratio of minimizing congestion. On the other hand, \({\varvec{3}-\textsf {STC}}\) can be solved in polynomial time, with the complexity status of this problem for \(K\in { \left\{ 4,5,6,7 \right\} }\) remaining an open problem. We substantially improve the earlier hardness results by proving that \({\varvec{K}-\textsf {STC}}\) is \(\mathbb{N}\mathbb{P}\)-complete for \(K\ge 5\). This leaves only the case \(K=4\) open, and improves the lower bound on the approximation ratio to 1.2. Motivated by evidence that minimizing congestion is hard even for graphs of small constant radius, we also consider \({\varvec{K}-\textsf {STC}}\) restricted to graphs of radius 2, and we prove that this variant is \(\mathbb{N}\mathbb{P}\)-complete for all \(K\ge 6\).

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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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