Computing Truncated Metric Dimension of Trees

TL;DR

This paper investigates the computational complexity of determining the $k$-truncated metric dimension of trees, proving NP-hardness for general $k$ and providing a polynomial-time algorithm for fixed $k$.

Contribution

It establishes NP-hardness for computing $k$-truncated metric dimension of trees and offers a polynomial-time algorithm for fixed $k$, advancing understanding of graph resolving sets.

Findings

NP-hardness for general $k$

Polynomial-time algorithm for fixed $k$

Enhanced understanding of truncated metric dimensions

Abstract

Let $G=(V,E)$ be a simple, unweighted, connected graph. Let $d(u,v)$ denote the distance between vertices $u,v$. A resolving set of $G$ is a subset $S$ of $V$ such that knowing the distance from a vertex $v$ to every vertex in $S$ uniquely identifies $v$. The metric dimension of $G$ is defined as the size of the smallest resolving set of $G$. We define the $k$-truncated resolving set and $k$-truncated metric dimension of a graph similarly, but with the notion of distance replaced with $d_k(u,v) := \min(d(u,v),k+1)$. In this paper, we demonstrate that computing $k$-truncated dimension of trees is NP-Hard for general $k$. We then present a polynomial-time algorithm to compute $k$-truncated dimension of trees when $k$ is a fixed constant.