Separator decompositions have proven to be useful for e cient parallel shortest-path computation. In this paper the applicability of separator decompositions to maximum ow computation is explored. It is shown that e cient parallel shortest-path computation can be incorporated in the shortest augmenting path maximum ow algorithm. A class of graphs is described for which the resulting algorithm takes O(n 2+ log n) time and O(n 3) work, where 0 < < 1 3 is a class-dependent constant. For graphs with bounded treewidth an NC-algorithm is known for the maximum ow problem. In this paper we show that width-O(1) tree decompositions and separator decompositions with separators, leaf vertex sets, and boundaries of O(1) size are equivalent notions...
The Minimum Size Tree Decomposition (MSTD) and Minimum Size Path Decomposition (MSPD) problems ask f...
We present an algorithm that takes ON I/Os (sort(N)=Θ((N/(DB)) log∈ M/B (N/B)) is the number of I/Os...
We show that the sparsest cut in graphs can be approximated within O(log 2 n) factor in Õ(n3/2) time...
Separator decompositions have proven to be useful for efficient parallel shortest- path computation...
We give the first NC algorithm for finding a clique separator decomposition of a graph, that is, a ...
We present faster algorithms for approximate maximum flow in undirected graphs with good separator s...
Many divide-and-conquer algorithms employ the fact that the vertex set of a graph of bounded treewid...
AbstractA network with vertices 1; …, n in which each arc has the form (i, j) with i < j is consider...
AbstractIt is shown that the problem of finding a maximal set of paths in a given (undirected or dir...
AbstractThis paper extends the author's parallel nested dissection algorithm (Pan and Reif, Technica...
In spite of intensive research, no work-efficient parallel algorithm for the single source shortest ...
We present I/O-efficient algorithms for the single source shortest path problem and NP-hard problems...
Branch & Reduce and dynamic programming on graphs of bounded treewidth are among the most common...
Abstract. For a weighted, undirected graph G = (V;E) where jV j = n and jEj = m, we examine the sing...
We study the problems of finding a subset of nodes having a given size k and satisfying one of the f...
The Minimum Size Tree Decomposition (MSTD) and Minimum Size Path Decomposition (MSPD) problems ask f...
We present an algorithm that takes ON I/Os (sort(N)=Θ((N/(DB)) log∈ M/B (N/B)) is the number of I/Os...
We show that the sparsest cut in graphs can be approximated within O(log 2 n) factor in Õ(n3/2) time...
Separator decompositions have proven to be useful for efficient parallel shortest- path computation...
We give the first NC algorithm for finding a clique separator decomposition of a graph, that is, a ...
We present faster algorithms for approximate maximum flow in undirected graphs with good separator s...
Many divide-and-conquer algorithms employ the fact that the vertex set of a graph of bounded treewid...
AbstractA network with vertices 1; …, n in which each arc has the form (i, j) with i < j is consider...
AbstractIt is shown that the problem of finding a maximal set of paths in a given (undirected or dir...
AbstractThis paper extends the author's parallel nested dissection algorithm (Pan and Reif, Technica...
In spite of intensive research, no work-efficient parallel algorithm for the single source shortest ...
We present I/O-efficient algorithms for the single source shortest path problem and NP-hard problems...
Branch & Reduce and dynamic programming on graphs of bounded treewidth are among the most common...
Abstract. For a weighted, undirected graph G = (V;E) where jV j = n and jEj = m, we examine the sing...
We study the problems of finding a subset of nodes having a given size k and satisfying one of the f...
The Minimum Size Tree Decomposition (MSTD) and Minimum Size Path Decomposition (MSPD) problems ask f...
We present an algorithm that takes ON I/Os (sort(N)=Θ((N/(DB)) log∈ M/B (N/B)) is the number of I/Os...
We show that the sparsest cut in graphs can be approximated within O(log 2 n) factor in Õ(n3/2) time...