We propose improved exact and heuristic algorithms for solving the maximum weight clique problem, a well-known problem in graph theory with many applications. Our algorithms interleave successful techniques from related work with novel data reduction rules that use local graph structure to identify and remove vertices and edges while retaining the optimal solution. We evaluate our algorithms on a range of synthetic and real-world graphs, and find that they outperform the current state of the art on most inputs. Our data reductions always produce smaller reduced graphs than existing data reductions alone. As a result, our exact algorithm, MWCRedu, finds solutions orders of magnitude faster on naturally weighted, medium-sized map labeling graphs and random hyperbolic graphs. Our heuristic algorithm, MWCPeel, outperforms its competitors on these instances, but is slightly less effective on extremely dense or large instances.
Improved Exact and Heuristic Algorithms for Maximum Weight Clique
Roman Erhardt,Kathrin Hanauer,Nils M. Kriege,Christian Schulz,Darren Strash
Published 2023 in arXiv.org
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- Publication year
2023
- Venue
arXiv.org
- Publication date
2023-02-01
- Fields of study
Mathematics, Computer Science
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