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

TL;DR

This paper introduces improved semi-streaming algorithms for the (1,2)-TSP, Max-TSP, and maximum path cover problems, achieving better approximation ratios with fewer passes over the data.

Contribution

It presents new semi-streaming algorithms that improve approximation ratios for (1,2)-TSP, Max-TSP, and maximum path cover problems, with efficient pass complexity.

Findings

Achieves a $(rac{2}{3}- ext{epsilon})$-approximation for maximum path cover.

Develops a $(rac{4}{3}+ ext{epsilon})$-approximation for (1,2)-TSP.

Provides a $(rac{7}{12}- ext{epsilon})$-approximation for Max-TSP.

Abstract

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 $\epsilon > 0$, achieves a $(\frac{2}{3}-\epsilon)$-approximation of the maximum path cover size for an $n$-vertex graph, using $\text{poly}(\frac{1}{\epsilon})$ 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 $(\frac{4}{3} + \epsilon)$, 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 $(\frac{7}{12} - \epsilon)$-approximation for Max-TSP in $\text{poly}(\frac{1}{\epsilon})$ passes, improving on the previously known $(\frac{1}{2}-\epsilon)$-approximation obtained via maximum weight matching in the semi-streaming model.