Linear Kernels and Linear-Time Algorithms for Finding Large Cuts

Abstract

The maximum cut problem in graphs and its generalizations are fundamental combinatorial problems. Several of these cut problems were recently shown to be fixed-parameter tractable and admit polynomial kernels when parameterized above the tight lower bound measured by the size and order of the graph. In this paper we continue this line of research and considerably improve several of those results:We show that an algorithm by Crowston et al. (Algorithmica 72(3):734–757, 2015) for (Signed) Max-Cut Above Edwards−Erdős Bound can be implemented so as to run in linear time8^kcdot O(m); this significantly improves the previous analysis with run time 8^kcdot O(n^4).We give an asymptotically optimal kernel for (Signed) Max-Cut Above Edwards−Erdős Bound with O(k) vertices, improving a kernel with O(k^3) vertices by Crowston et al. (Theor Comput Sci 513:53–64, 2013).We improve all known kernels for parameterizations above strongly lambda -extendible properties (a generalization of the Max-Cut results) by Crowston et al. (Proceedings of FSTTCS 2013, Leibniz international proceedings in informatics, Guwahati, 2013) from O(k^3) vertices to O(k) vertices.Therefore, Max Acyclic Subdigraph parameterized above Poljak–Turzík bound admits a kernel with O(k) vertices and can be solved in 2^{O(k)}cdot n^{O(1)} time; this answers an open question by Crowston et al. (Proceedings of FSTTCS 2012, Leibniz international proceedings in informatics, Hyderabad, 2012). All presented kernels can be computed in time O(km).