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IJCAI 2017

A Partitioning Algorithm for Maximum Common Subgraph Problems

Conference Paper Constraints and Satisfiability Artificial Intelligence

Abstract

We introduce a new branch and bound algorithm for the maximum common subgraph and maximum common connected subgraph problems which is based around vertex labelling and partitioning. Our method in some ways resembles a traditional constraint programming approach, but uses a novel compact domain store and supporting inference algorithms which dramatically reduce the memory and computation requirements during search, and allow better dual viewpoint ordering heuristics to be calculated cheaply. Experiments show a speedup of more than an order of magnitude over the state of the art, and demonstrate that we can operate on much larger graphs without running out of memory.

Authors

Keywords

  • Combinatorial & Heuristic Search: Combinatorial search/optimisation
  • Constraints and Satisfiability: Constraint Optimisation
  • Constraints and Satisfiability: Constraint Satisfaction

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
272025217638762116
v2026.09.13