A Fast Heuristic for Stochastic Steiner Tree Problems
Abstract
Network design under uncertainty arises in countless real-world settings and can be captured by the Stochastic Steiner Tree Problem (SSTP). Although there are a few approaches specifically tailored to this stochastic optimization problem, there are considerably more state-of-the-art heuristics for its deterministic variant, the Steiner Tree Problem (STP). In this work, we show how to leverage an existing STP heuristic in building a novel method for solving its stochastic variant, the SSTP. This approach is a powerful, yet simple and easy-to-implement way of solving this complex problem. We test our method using benchmark instances from the literature. Numerical results show considerably faster computation times compared to the state-of-the-art, with a gap of approximately 5%.
Cite
@article{arxiv.2602.23858,
title = {A Fast Heuristic for Stochastic Steiner Tree Problems},
author = {Berend Markhorst and Alessandro Zocca and Joost Berkhout and Rob van der Mei},
journal= {arXiv preprint arXiv:2602.23858},
year = {2026}
}