On the performance of a cavity method based algorithm for the Prize-Collecting Steiner Tree Problem on graphs

TL;DR

This paper evaluates a cavity method-based algorithm for the Prize-Collecting Steiner Tree problem, demonstrating its superior performance over existing heuristics and solvers in large graph instances.

Contribution

It introduces a cavity method algorithm for PCST, showing its effectiveness and optimality properties compared to state-of-the-art methods.

Findings

Outperforms existing heuristics and solvers in large instances

Offers faster solutions with higher quality

Proves certain optimality properties of the solutions

Abstract

We study the behavior of an algorithm derived from the cavity method for the Prize-Collecting Steiner Tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks networks and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the DHEA solver, a Branch and Cut Linear/Integer Programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two post-processing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.