70 research outputs found
Linear-time algorithms for scattering number and Hamilton-connectivity of interval graphs.
We prove that for all inline image an interval graph is inline image-Hamilton-connected if and only if its scattering number is at most k. This complements a previously known fact that an interval graph has a nonnegative scattering number if and only if it contains a Hamilton cycle, as well as a characterization of interval graphs with positive scattering numbers in terms of the minimum size of a path cover. We also give an inline image time algorithm for computing the scattering number of an interval graph with n vertices and m edges, which improves the previously best-known inline image time bound for solving this problem. As a consequence of our two results, the maximum k for which an interval graph is k-Hamilton-connected can be computed in inline image time
Computing and counting longest paths on circular-arc graphs in polynomial time.
The longest path problem asks for a path with the largest number of vertices in a given graph. The first polynomial time algorithm (with running time O(n4)) has been recently developed for interval graphs. Even though interval and circular-arc graphs look superficially similar, they differ substantially, as circular-arc graphs are not perfect. In this paper, we prove that for every path P of a circular-arc graph G, we can appropriately “cut” the circle, such that the obtained (not induced) interval subgraph G′ of G admits a path P′ on the same vertices as P. This non-trivial result is of independent interest, as it suggests a generic reduction of a number of path problems on circular-arc graphs to the case of interval graphs with a multiplicative linear time overhead of O(n). As an application of this reduction, we present the first polynomial algorithm for the longest path problem on circular-arc graphs, which turns out to have the same running time O(n4) with the one on interval graphs, as we manage to get rid of the linear overhead of the reduction. This algorithm computes in the same time an n-approximation of the number of different vertex sets that provide a longest path; in the case where G is an interval graph, we compute the exact number. Moreover, our algorithm can be directly extended with the same running time to the case where every vertex has an arbitrary positive weight
Linear Time LexDFS on Cocomparability Graphs
Lexicographic depth first search (LexDFS) is a graph search protocol which
has already proved to be a powerful tool on cocomparability graphs.
Cocomparability graphs have been well studied by investigating their
complements (comparability graphs) and their corresponding posets. Recently
however LexDFS has led to a number of elegant polynomial and near linear time
algorithms on cocomparability graphs when used as a preprocessing step [2, 3,
11]. The nonlinear runtime of some of these results is a consequence of
complexity of this preprocessing step. We present the first linear time
algorithm to compute a LexDFS cocomparability ordering, therefore answering a
problem raised in [2] and helping achieve the first linear time algorithms for
the minimum path cover problem, and thus the Hamilton path problem, the maximum
independent set problem and the minimum clique cover for this graph family
Linear-Time Algorithms for Scattering Number and Hamilton-Connectivity of Interval Graphs
We show that for all k ≤ − 1 an interval graph is − (k + 1)-Hamilton-connected if and only if its scattering number is at most k. We also give an O(n + m) time algorithm for computing the scattering number of an interval graph with n vertices and m edges, which improves the O(n 3) time bound of Kratsch, Kloks and Müller. As a consequence of our two results the maximum k for which an interval graph is k-Hamilton-connected can be computed in O(n + m) time
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