The Complexity of Maximum $k$-Order Bounded Component Set Problem

TL;DR

This paper investigates the computational difficulty of the Max-$k$-OBCS problem, establishing strong hardness results and proposing a generalized Turán-based approximation algorithm with performance guarantees.

Contribution

It proves new hardness bounds for Max-$k$-OBCS, extending previous results, and generalizes Turán's greedy algorithm for better approximation guarantees.

Findings

Max-$k$-OBCS is hard to approximate within $n^{1- ext{epsilon}}$ for constant $k$.

Provides lower bounds on approximability when $k$ varies.

Generalizes Turán's algorithm with an approximation factor depending on $k$ and average degree.

Abstract

Given a graph $G=(V, E)$ and a positive integer $k$, in Maximum $k$-Order Bounded Component Set (Max-$k$-OBCS), it is required to find a vertex set $S \subseteq V$ of maximum size such that each component in the induced graph $G[S]$ has at most $k$ vertices. We prove that for constant $k$, Max-$k$-OBCS is hard to approximate within a factor of $n^{1 -\epsilon}$, for any $\epsilon > 0$, unless $\mathsf{P} = \mathsf{NP}$. This is an improvement on the previous lower bound of $\sqrt{n}$ for Max-2-OBCS due to Orlovich et al. We provide lower bounds on the approximability when $k$ is not a constant as well. Max-$k$-OBCS can be seen as a generalization of Maximum Independent Set (Max-IS). We generalize Tur\'an's greedy algorithm for Max-IS and prove that it approximates Max-$k$-OBCS within a factor of $(2k - 1)\overline{d} + k$, where $\overline{d}$ is the average degree of the input graph $G$. This approximation factor is a generalization of Tur\'an's approximation factor for Max-IS.