Learning to Prune Instances of Steiner Tree Problem in Graphs
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 year...
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| Main Authors | , |
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| Format | Journal Article |
| Language | English |
| Published |
25.08.2022
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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. |
|---|---|
| AbstractList | 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. |
| Author | Ajwani, Deepak Zhang, Jiwei |
| Author_xml | – sequence: 1 givenname: Jiwei surname: Zhang fullname: Zhang, Jiwei – sequence: 2 givenname: Deepak surname: Ajwani fullname: Ajwani, Deepak |
| BackLink | https://doi.org/10.48550/arXiv.2208.11985$$DView paper in arXiv |
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| Snippet | 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... |
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| SubjectTerms | Computer Science - Artificial Intelligence Computer Science - Data Structures and Algorithms Computer Science - Discrete Mathematics Computer Science - Learning |
| Title | Learning to Prune Instances of Steiner Tree Problem in Graphs |
| URI | https://arxiv.org/abs/2208.11985 |
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