2017-08-16

# On the integrality gap of the prize-collecting Steiner forest LP

## Publication

### Publication

*Presented at the International Workshop on Approximation Algorithms for Combinatorial Optimization (August 2017), Berkeley*

In the prize-collecting Steiner forest (PCSF) problem, we are given an undirected graph G = (V,E), edge costs {ce φ 0}e2E, terminal pairs {(si, ti)}ki =1, and penalties {i}ki =1 for each terminal pair; the goal is to find a forest F to minimize c(F) + P i:(si,ti) not connected in F i. The Steiner forest problem can be viewed as the special case where i = 1 for all i. It was widely believed that the integrality gap of the natural (and well-studied) linear-programming (LP) relaxation for PCSF (PCSF-LP) 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.

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doi.org/10.4230/LIPIcs.APPROX-RANDOM.2017.17 | |

International Workshop on Approximation Algorithms for Combinatorial Optimization | |

Organisation | Centrum Wiskunde & Informatica, Amsterdam, The Netherlands |

Könemann, J, Olver, N.K, Pashkovich, K, Ravi, R, Swamy, C, & Vygen, J. (2017). On the integrality gap of the prize-collecting Steiner forest LP. In
Leibniz International Proceedings in Informatics, LIPIcs. doi:10.4230/LIPIcs.APPROX-RANDOM.2017.17 |