JOURNAL ARTICLE
Approximation Algorithms for Partial Vertex Covers in Trees.
Published In: International Journal of Foundations of Computer Science, 2024, v. 35, n. 4. P. 387 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mkrtchyan, Vahan; Parekh, Ojas; Subramani, K. 3 of 3
Abstract
This paper is concerned with designing algorithms for and analyzing the computational complexity of the partial vertex cover problem in trees. Graphs (and trees) are frequently used to model risk management in various systems. In particular, Caskurlu et al. in [4] have considered a system which essentially represents a tripartite graph. The goal in this model is to reduce the risk in the system below a predefined risk threshold level. It can be shown that the main goal in this risk management system can be formulated as a Partial Vertex Cover problem on bipartite graphs. In this paper, we focus on a special case of the partial vertex cover problem, when the input graph is a tree. We consider four possible versions of this setting, depending on whether or not, the vertices and edges are weighted. Two of these versions, where edges are assumed to be unweighted, are known to be polynomial-time solvable. However, the computational complexity of this problem with weighted edges, and possibly with weighted vertices, remained open. The main contribution of this paper is to resolve these questions by fully characterizing which variants of partial vertex cover remain NP-hard in trees, and which can be solved in polynomial time. In the paper, we propose two pseudo-polynomial DP-based algorithms for the most general case in which weights are present on both the edges and the vertices of the tree. One of these algorithms leads to a polynomial-time procedure, when weights are confined to the edges of the tree. The insights used in this algorithm are combined with additional scaling ideas to derive an FPTAS for the general case. A secondary contribution of this work is to propose a novel way of using centroid decompositions in trees, which could be useful in other settings as well. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Foundations of Computer Science. 2024/06, Vol. 35, Issue 4, p387
- Document Type:Article
- Subject Area:Computer Science
- Publication Date:2024
- ISSN:0129-0541
- DOI:10.1142/S0129054123500089
- Accession Number:177778571
- Copyright Statement:Copyright of International Journal of Foundations of Computer Science is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.