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Kernelization in Parameterized Computation: A Survey

Kernelization in Parameterized Computation: A Survey
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摘要 Parameterized computation is a new method dealing with NP-hard problems, which has attracted a lot of attentions in theoretical computer science. As a practical preprocessing method for NP-hard problems, kernelizaiton in parameterized computation has recently become an active research area. In this paper, we discuss several kernelizaiton techniques, such as crown decomposition, planar graph vertex partition, randomized methods, and kernel lower bounds, which have been used widely in the kernelization of many hard problems. Parameterized computation is a new method dealing with NP-hard problems, which has attracted a lot of attentions in theoretical computer science. As a practical preprocessing method for NP-hard problems, kernelizaiton in parameterized computation has recently become an active research area. In this paper, we discuss several kernelizaiton techniques, such as crown decomposition, planar graph vertex partition, randomized methods, and kernel lower bounds, which have been used widely in the kernelization of many hard problems.
出处 《Tsinghua Science and Technology》 SCIE EI CAS 2014年第4期338-345,共8页 清华大学学报(自然科学版(英文版)
基金 supported by the National Natural Science Foundation of China (Nos. 61173051, 61103033, and 61232001)
关键词 parameterized computation kernelization parameterized algorithm NP-hard parameterized computation kernelization parameterized algorithm NP-hard
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