Abstract
Since its inception in the 1990’s, parameterized complexity has established itself as one of the major research areas in theoretical computer science. Parameterized and kernelization algorithms have proved to be very useful for solving important problems in various domains of science and technology. Moreover, parameterized complexity has shown deep connections to traditional areas of theoretical computer science, such as structural complexity theory and approximation algorithms.
In this paper, we discuss some of the recent results pertaining to the relation between parameterized complexity and subexponential-time computability. We focus our attention on satisfiability problems because they play a key role in the definition of both parameterized complexity and structural complexity classes, and because they model numerous important problems in computer science.
This paper is dedicated to the 60th birthday of Michael R. Fellows. Many of the results examined in this paper were authored or co-authored by Michael, and those that were not, would probably never have existed without his efforts. If parameterized complexity would not have started without Michael, Rodney, and two bottles of 1989 Villa Maria Merlot/Cabarnet Sauvignon, then it definitely would not have flourished and matured into such an important area of theoretical computer science without Michael’s great ideas, efforts, and inspirations.
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Chen, J., Kanj, I.A. (2012). Parameterized Complexity and Subexponential-Time Computability. In: Bodlaender, H.L., Downey, R., Fomin, F.V., Marx, D. (eds) The Multivariate Algorithmic Revolution and Beyond. Lecture Notes in Computer Science, vol 7370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30891-8_11
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