# On the Integrality Gap of the Prize-Collecting Steiner Forest LP

## TL;DR

This paper proves that the natural LP relaxation for the prize-collecting Steiner forest problem has an integrality gap of at least 9/4, challenging previous beliefs and highlighting limitations of LP-based approximation methods.

## Contribution

It establishes a new lower bound on the integrality gap for the LP relaxation of PCSF and shows limitations of Lagrangian-multiplier-preserving algorithms, also analyzing the prize-collecting Steiner tree case.

## Key findings

- Integrality gap of LP relaxation for PCSF is at least 9/4.
- No LMP algorithm can achieve better than 4-approximation using this LP.
- For PCST, all basic feasible solutions have variables at most 1/3, limiting iterative rounding approaches.

## Abstract

In the prize-collecting Steiner forest (PCSF) problem, we are given an undirected graph $G=(V,E)$, edge costs $\{c_e\geq 0\}_{e\in E}$, terminal pairs $\{(s_i,t_i)\}_{i=1}^k$, and penalties $\{\pi_i\}_{i=1}^k$ for each terminal pair; the goal is to find a forest $F$ to minimize $c(F)+\sum_{i: (s_i,t_i)\text{ not connected in }F}\pi_i$. The Steiner forest problem can be viewed as the special case where $\pi_i=\infty$ for all $i$. It was widely believed that the integrality gap of the natural (and well-studied) linear-programming (LP) relaxation for PCSF is at most 2. We dispel this belief by showing that the integrality gap of this LP is at least $9/4$. This holds even for planar graphs. We also show that using this LP, one cannot devise a Lagrangian-multiplier-preserving (LMP) algorithm with approximation guarantee better than $4$. Our results thus show a separation between the integrality gaps of the LP-relaxations for prize-collecting and non-prize-collecting (i.e., standard) Steiner forest, as well as the approximation ratios achievable relative to the optimal LP solution by LMP- and non-LMP- approximation algorithms for PCSF. For the special case of prize-collecting Steiner tree (PCST), we prove that the natural LP relaxation admits basic feasible solutions with all coordinates of value at most $1/3$ and all edge variables positive. Thus, we rule out the possibility of approximating PCST with guarantee better than $3$ using a direct iterative rounding method.