Finding a maximum clique in an arbitrary graph
SIAM Journal on Computing
New methods to color the vertices of a graph
Communications of the ACM
Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Constraint Programming Based Column Generation for Crew Assignment
Journal of Heuristics
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
A Framework for Constraint Programming Based Column Generation
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Cutting Planes in Constraint Programming: A Hybrid Approach
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Exact Solution of the Quadratic Knapsack Problem
INFORMS Journal on Computing
An algorithm for finding a maximum clique in a graph
Operations Research Letters
Exploiting semidefinite relaxations in constraint programming
Computers and Operations Research
A logical approach to efficient Max-SAT solving
Artificial Intelligence
Simple ingredients leading to very efficient heuristics for the maximum clique problem
Journal of Heuristics
k-Clustering Minimum Biclique Completion via a Hybrid CP and SDP Approach
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Finding Top-N Pseudo Formal Concepts with Core Intents
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
Extended and discretized formulations for the maximum clique problem
Computers and Operations Research
Mining the Largest Dense Vertexlet in a Weighted Scale-free Graph
Fundamenta Informaticae
An extended branch and bound search algorithm for finding top-N formal concepts of documents
JSAI'06 Proceedings of the 20th annual conference on New frontiers in artificial intelligence
A Max-SAT inference-based pre-processing for Max-clique
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
A new approach to the stable set problem based on ellipsoids
IPCO'11 Proceedings of the 15th international conference on Integer programming and combinatoral optimization
A new approach for solving the maximum clique problem
AAIM'06 Proceedings of the Second international conference on Algorithmic Aspects in Information and Management
A method for pinpoint clustering of web pages with pseudo-clique search
Proceedings of the 2005 international conference on Federation over the Web
An algorithm for extracting rare concepts with concise intents
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
Finding significant web pages with lower ranks by pseudo-clique search
DS'05 Proceedings of the 8th international conference on Discovery Science
RelView: an OBDD-based computer algebra system for relations
CASC'05 Proceedings of the 8th international conference on Computer Algebra in Scientific Computing
A simple and faster branch-and-bound algorithm for finding a maximum clique
WALCOM'10 Proceedings of the 4th international conference on Algorithms and Computation
NuMVC: an efficient local search algorithm for minimum vertex cover
Journal of Artificial Intelligence Research
Improvements to MCS algorithm for the maximum clique problem
Journal of Combinatorial Optimization
Speeding up branch and bound algorithms for solving the maximum clique problem
Journal of Global Optimization
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We consider a branch-and-bound algorithm for maximum clique problems. We introduce cost based filtering techniques for the so-called candidate set (i.e. a set of nodes that can possibly extend the clique in the current choice point).Additionally, we present a taxonomy of upper bounds for maximum clique. Analytical results show that our cost based filtering is in a sense as tight as most of these well-known bounds for the maximum clique problem.Experiments demonstrate that the combination of cost based filtering and vertex coloring bounds outperforms the old approach as well as approaches that only apply either of these techniques. Furthermore, the new algorithm is competitive with other recent algorithms for maximum clique.