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Combining Efficient Preprocessing and Incremental MaxSAT Reasoning for MaxClique in Large Graphs

AuthorsJiang, Hua; Li, Chu Min; Manyà, Felip
Large MaxClique
Issue Date29-Aug-2016
PublisherIOS Press
Citation22nd European Conference on Artificial Intelligence, ECAI 2016; FAIA Vol. 285 (2016): 939-947
AbstractWe describe a new exact algorithm for MaxClique, called LMC (short for Large MaxClique), that is especially suited for large sparse graphs. LMC is competitive because it combines an efficient preprocessing procedure and incremental MaxSAT reasoning in a branch-and-bound scheme. The empirical results show that LMC outperforms existing exact MaxClique algorithms on large sparse graphs from real-world applications. © 2016 The Authors and IOS Press.This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
Identifiersdoi: 10.3233/978-1-61499-672-9-939
isbn: 978-1-61499-672-9
Appears in Collections:(IIIA) Comunicaciones congresos
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