On Problems as Hard as CNF-SAT

CCC '12 Proceedings of the 2012 IEEE Conference on Computational Complexity (CCC)(2016)

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摘要
The field of exact exponential time algorithms for NP-hard problems has thrived over the last decade. While exhaustive search remains asymptotically the fastest known algorithm for some basic problems, difficult and non-trivial exponential time algorithms have been found for a myriad of problems, including Graph Coloring, Hamiltonian Path, Dominating Set and 3-CNF-Sat. In some instances, improving these algorithms further seems to be out of reach. The CNF-Sat problem is the canonical example of a problem for which the trivial exhaustive search algorithm runs in time O(2^n), where n is the number of variables in the input formula. While there exist non-trivial algorithms for CNF-Sat that run in time o(2^n), no algorithm was able to improve the growth rate 2 to a smaller constant, and hence it is natural to conjecture that 2 is the optimal growth rate. The strong exponential time hypothesis (SETH) by Impagliazzo and Paturi [JCSS 2001] goes a little bit further and asserts that, for every epsilon
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fastest known algorithm,non-trivial exponential time algorithm,basic problem,trivial exhaustive search algorithm,non-trivial algorithm,exact exponential time algorithm,cnf-sat problem,time o,strong exponential time hypothesis,np-hard problem,computational complexity,force,subset sum,set cover,algorithm design and analysis,hamiltonian path,set theory,np hard problems,graph theory,graph coloring,steiner trees,dominating set
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