Operations Research 2025
Abstract Submission

2356. On Solving the Stochastic Steiner Tree Problem with a Fast Heuristic

Invited abstract in session WB-4: Network Optimization, stream Discrete and Combinatorial Optimization.

Wednesday, 10:45-12:15
Room: H6

Authors (first author is the speaker)

1. Berend Markhorst
Stochastics Group, CWI
2. Alessandro Zocca
CMS, California Institute of Technology
3. Joost Berkhout
Vrije Universiteit Amsterdam
4. Rob van der Mei
CWI

Abstract

The Stochastic Steiner Tree Problem (SSTP) is well-known in the literature and has many applications. 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 equivalent, the Steiner Tree Problem (STP). In this work, we show how to use one of these STP heuristics in a novel framework to solve the SSTP. This approach is a powerful, yet simple and easy-to-implement way of solving this complex problem. We test our method with benchmark instances from the literature and the numerical results show considerably faster computation times compared to the current state-of-the-art, with an optimality loss of approximately 5%.

Keywords

Status: accepted


Back to the list of papers