关于最小解析支配集问题的贪婪近似算法

IF 0.9 4区数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Combinatorial Optimization Pub Date : 2024-10-28 DOI:10.1007/s10878-024-01229-4

Hao Zhong

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引用次数: 0

摘要

本文研究的最小解析支配集问题是一般图中一个新兴的组合优化问题。我们证明了解析支配集问题是 NP-困难的，并提出了一种贪婪算法，该算法通过建立一个亚模态势函数（其中 n 是输入图的节点数），近似率为 (\(1 + 2\ln n\)) 。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

On greedy approximation algorithm for the minimum resolving dominating set problem

查看原文本刊更多论文

On greedy approximation algorithm for the minimum resolving dominating set problem

In this paper, we investigate the minimum resolving dominating set problem which is a emerging combinatorial optimization problem in general graphs. We prove that the resolving dominating set problem is NP-hard and propose a greedy algorithm with an approximation ratio of (\(1 + 2\ln n\)) by establishing a submodular potential function, where n is the node number of the input graph.

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来源期刊

Journal of Combinatorial Optimization 数学-计算机：跨学科应用

CiteScore

2.00

自引率

10.00%

发文量

审稿时长

6 months

期刊介绍： The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.