2-Approximation for Prize-Collecting Steiner Forest

Approximation algorithms for the prize-collecting Steiner forest problem (PCSF) have been a subject of research for over three decades, starting with the seminal works of Agrawal, Klein, and Ravi [1, 2] and Goemans and Williamson [15, 16] on Steiner forest and prize-collecting problems. In this paper, we propose and analyze a natural deterministic algorithm for PCSF that achieves a 2-approximate solution in polynomial time. This represents a significant improvement compared to the previously best known algorithm with a 2.54-approximation factor developed by Hajiaghayi and Jain [20] in 2006. Furthermore, Könemann, Olver, Pashkovich, Ravi, Swamy, and Vygen [25] have established an integrality gap of at least 9/4 for the natural LP relaxation for PCSF. However, we surpass this gap through the utilization of an iterative algorithm and a novel analysis technique. Since 2 is the best known approximation guarantee for Steiner forest problem [2] (see also [16]), which is a special case of PCSF, our result matches this factor and closes the gap between the Steiner forest problem and its generalized version, PCSF.