Complexity of Multiple-Hamiltonicity in Graphs of Bounded Degree

TL;DR

This paper investigates the computational complexity of a generalized Hamiltonian cycle problem in graphs with bounded degree, providing characterizations of when the problem is polynomial-time solvable or NP-hard.

Contribution

It offers tight complexity classifications for the problem in regular and bounded-degree graphs, extending known results beyond Hamiltonicity.

Findings

NP-hardness for general parameters in bounded-degree graphs

Polynomial-time algorithms for specific parameter ranges

Tight characterizations for regular and bounded-degree graphs

Abstract

We study the following generalization of the Hamiltonian cycle problem: Given integers $a,b$ and graph $G$, does there exist a closed walk in $G$ that visits every vertex at least $a$ times and at most $b$ times? Equivalently, does there exist a connected $[2a,2b]$ factor of $2b \cdot G$ with all degrees even? This problem is NP-hard for any constants $1 \leq a \leq b$. However, the graphs produced by known reductions have maximum degree growing linearly in $b$. The case $a = b = 1 $ -- i.e. Hamiltonicity -- remains NP-hard even in $3$-regular graphs; a natural question is whether this is true for other $a$, $b$. In this work, we study which $a, b$ permit polynomial time algorithms and which lead to NP-hardness in graphs with constrained degrees. We give tight characterizations for regular graphs and graphs of bounded max-degree, both directed and undirected.