Finding a maximum clique in an arbitrary graph
SIAM Journal on Computing
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
On the Complexity of Approximating the Independent Set Problem
STACS '89 Proceedings of the 6th Annual Symposium on Theoretical Aspects of Computer Science
A column generation and branch-and-cut algorithm for the channel assignment problem
Computers and Operations Research
Exploiting incomplete information to manage multiprocessor tasks with variable arrival rates
Computers and Operations Research
On the asymmetric representatives formulation for the vertex coloring problem
Discrete Applied Mathematics
A nearly optimal sensor placement algorithm for boundary coverage
Pattern Recognition
A new lower bound for evaluating the performances of sensor location algorithms
Pattern Recognition Letters
A relational approach to functional decomposition of logic circuits
ACM Transactions on Database Systems (TODS)
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
An algorithm for finding a maximum clique in a graph
Operations Research Letters
Subgraph extraction and metaheuristics for the maximum clique problem
Journal of Heuristics
Modeling affiliations in networks
Proceedings of the Winter Simulation Conference
Bin Packing with Conflicts: A Generic Branch-and-Price Algorithm
INFORMS Journal on Computing
An adaptive multistart tabu search approach to solve the maximum clique problem
Journal of Combinatorial Optimization
Computational Optimization and Applications
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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A partially enumerative algorithm is presented for the maximum clique problem which is very simple to implement. Computational results for an efficient implementation on an IBM 3090 computer are provided for randomly generated graphs with up to 3000 vertices and over one million edges. Also provided are exact specifications for test problems to facilitate future comparisons. In addition, the Fortran 77 code of the proposed algorithm is given.