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arXiv · 2208.11985

Learning to Prune Instances of Steiner Tree Problem in Graphs

Jiwei Zhang·Deepak Ajwani
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Abstract

We consider the Steiner tree problem on graphs where we are given a set of nodes and the goal is to find a tree sub-graph of minimum weight that contains all nodes in the given set, potentially including additional nodes. This is a classical NP-hard combinatorial optimisation problem. In recent years, a machine learning framework called learning-to-prune has been successfully used for solving a diverse range of combinatorial optimisation problems. In this paper, we use this learning framework on the Steiner tree problem and show that even on this problem, the learning-to-prune framework results in computing near-optimal solutions at a fraction of the time required by commercial ILP solvers. Our results underscore the potential of the learning-to-prune framework in solving various combinatorial optimisation problems.

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BibTeXRIS

Jiwei Zhang, Deepak Ajwani. 2022-08-25. Learning to Prune Instances of Steiner Tree Problem in Graphs. https://doi.org/10.48786/inoc.2024.08

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