1 research outputs found

    Linear Recognition of Almost Interval Graphs

    Full text link
    Let \mbox{interval} + k v, \mbox{interval} + k e, and \mbox{interval} - k e denote the classes of graphs that can be obtained from some interval graph by adding kk vertices, adding kk edges, and deleting kk edges, respectively. When kk is small, these graph classes are called almost interval graphs. They are well motivated from computational biology, where the data ought to be represented by an interval graph while we can only expect an almost interval graph for the best. For any fixed kk, we give linear-time algorithms for recognizing all these classes, and in the case of membership, our algorithms provide also a specific interval graph as evidence. When kk is part of the input, these problems are also known as graph modification problems, all NP-complete. Our results imply that they are fixed-parameter tractable parameterized by kk, thereby resolving the long-standing open problem on the parameterized complexity of recognizing \mbox{interval}+ k e, first asked by Bodlaender et al. [Bioinformatics, 11:49--57, 1995]. Moreover, our algorithms for recognizing \mbox{interval}+ k v and \mbox{interval}- k e run in times O(6kβ‹…(n+m))O(6^k \cdot (n + m)) and O(8kβ‹…(n+m))O(8^k \cdot (n + m)), (where nn and mm stand for the numbers of vertices and edges respectively in the input graph,) significantly improving the O(k2kβ‹…n3m)O(k^{2k}\cdot n^3m)-time algorithm of Heggernes et al. [STOC 2007] and the O(10kβ‹…n9)O(10^k \cdot n^9)-time algorithm of Cao and Marx [SODA 2014] respectively.Comment: Completely restructured, and results on unit interval graphs have been dropped to make this version more focuse
    corecore