Improved Approximation Algorithms for (1,2)-TSP and Max-TSP Using Path Covers in the Semi-Streaming Model

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Autores principales: Alipour, Sharareh, Farokhnejad, Ermiya, Mömke, Tobias
Formato: Preprint
Publicado: 2025
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author Alipour, Sharareh
Farokhnejad, Ermiya
Mömke, Tobias
author_facet Alipour, Sharareh
Farokhnejad, Ermiya
Mömke, Tobias
contents We investigate semi-streaming algorithms for the Traveling Salesman Problem (TSP). Specifically, we focus on a variant known as the $(1,2)$-TSP, where the distances between any two vertices are either one or two. Our primary emphasis is on the closely related Maximum Path Cover Problem, which aims to find a collection of vertex-disjoint paths that cover the maximum number of edges in a graph. We propose an algorithm that, for any $ε> 0$, achieves a $(\frac{2}{3}-ε)$-approximation of the maximum path cover size for an $n$-vertex graph, using $\text{poly}(\frac{1}ε)$ passes. This result improves upon the previous $\frac{1}{2}$-approximation by Behnezhad et al. [ICALP 2024] in the semi-streaming model. Building on this result, we design a semi-streaming algorithm that constructs a tour for an instance of $(1,2)$-TSP with an approximation factor of $(\frac{4}{3} + ε)$, improving upon the previous $\frac{3}{2}$-approximation actor algorithm by Behnezhad et al. [ICALP 2024] (Although it is not explicitly stated in the paper that their algorithm works in the semi-streaming model, it is easy to verify). Furthermore, we extend our approach to develop an approximation algorithm for the Maximum TSP (Max-TSP), where the goal is to find a Hamiltonian cycle with the maximum possible weight in a given weighted graph $G$. Our algorithm provides a $(\frac{7}{12} - ε)$-approximation for Max-TSP in $\text{poly}(\frac{1}ε)$ passes, improving on the previously known $(\frac{1}{2}-ε)$-approximation obtained via maximum weight matching in the semi-streaming model.
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id arxiv_https___arxiv_org_abs_2501_04813
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Improved Approximation Algorithms for (1,2)-TSP and Max-TSP Using Path Covers in the Semi-Streaming Model
Alipour, Sharareh
Farokhnejad, Ermiya
Mömke, Tobias
Data Structures and Algorithms
We investigate semi-streaming algorithms for the Traveling Salesman Problem (TSP). Specifically, we focus on a variant known as the $(1,2)$-TSP, where the distances between any two vertices are either one or two. Our primary emphasis is on the closely related Maximum Path Cover Problem, which aims to find a collection of vertex-disjoint paths that cover the maximum number of edges in a graph. We propose an algorithm that, for any $ε> 0$, achieves a $(\frac{2}{3}-ε)$-approximation of the maximum path cover size for an $n$-vertex graph, using $\text{poly}(\frac{1}ε)$ passes. This result improves upon the previous $\frac{1}{2}$-approximation by Behnezhad et al. [ICALP 2024] in the semi-streaming model. Building on this result, we design a semi-streaming algorithm that constructs a tour for an instance of $(1,2)$-TSP with an approximation factor of $(\frac{4}{3} + ε)$, improving upon the previous $\frac{3}{2}$-approximation actor algorithm by Behnezhad et al. [ICALP 2024] (Although it is not explicitly stated in the paper that their algorithm works in the semi-streaming model, it is easy to verify). Furthermore, we extend our approach to develop an approximation algorithm for the Maximum TSP (Max-TSP), where the goal is to find a Hamiltonian cycle with the maximum possible weight in a given weighted graph $G$. Our algorithm provides a $(\frac{7}{12} - ε)$-approximation for Max-TSP in $\text{poly}(\frac{1}ε)$ passes, improving on the previously known $(\frac{1}{2}-ε)$-approximation obtained via maximum weight matching in the semi-streaming model.
title Improved Approximation Algorithms for (1,2)-TSP and Max-TSP Using Path Covers in the Semi-Streaming Model
topic Data Structures and Algorithms
url https://arxiv.org/abs/2501.04813