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arXiv · 1905.05840

A Learning based Branch and Bound for Maximum Common Subgraph Problems

Yan-li Liu·Chu-min Li·Hua Jiang·Kun He
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Abstract

Branch-and-bound (BnB) algorithms are widely used to solve combinatorial problems, and the performance crucially depends on its branching heuristic.In this work, we consider a typical problem of maximum common subgraph (MCS), and propose a branching heuristic inspired from reinforcement learning with a goal of reaching a tree leaf as early as possible to greatly reduce the search tree size.Extensive experiments show that our method is beneficial and outperforms current best BnB algorithm for the MCS.

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Yan-li Liu, Chu-min Li, Hua Jiang, Kun He. 2019-05-15. A Learning based Branch and Bound for Maximum Common Subgraph Problems. https://arxiv.org/abs/1905.05840

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