An O(20.304n) Algorithm for Solving Maximum Independent Set Problem
IEEE Transactions on Computers
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition)
Measure and conquer: a simple O(20.288n) independent set algorithm
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
An Efficient Branch-and-bound Algorithm for Finding a Maximum Clique with Computational Experiments
Journal of Global Optimization
Parameterized Complexity
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Recent advances in algorithm design have shown a growing interest in seeking exact solutions to many hard problems. This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. Different algorithms adopt different branching and pruning techniques in order to reduce the unavoidable exponential growth in run time. This paper is concerned with another time-saving approach by developing new methods for exploiting high-performance computational platforms. A load balancing strategy is presented that could exploit multi-core architectures, such as clusters of symmetric multiprocessors. The well-known Maximum Clique problem is used as an exemplar to illustrate the utility of our approach.