Stronger path-based extended formulation for the Steiner tree problem

The Steiner tree problem (STP) is a classical NP-hard combinatorial optimization problem with applications in computational biology and network wiring. The objective of this problem is to find a minimum cost subgraph of a given undirected graph G with edge costs, that spans a subset of vertices called terminals. We present currently used linear programming formulations of the problem based on two different approaches—the bidirected cut relaxation (BCR) and the hypergraphic formulations (HYP), the former offering better computational performance, and the latter better bounds on the integrality gap. As our contribution, we propose a new hierarchy of path-based extended formulations for STP. We show that this hierarchy provides better integrality gaps on graph instances used to define the worst-case lower bounds on the integrality gap for both BCR and HYP. We prove that each consecutive level of our hierarchy is at least as strong as the previous one. Additionally, we also present numerical results showing that several difficult STP instances can be solved to integer optimality by using this hierarchy. Our approach can be adapted to variants of STP or applied to hypergraphic formulations for further potential improvement on the integrality gap bounds, in exchange for additional computational effort