1980
DOI: 10.1145/322217.322220
|View full text |Cite
|
Sign up to set email alerts
|

An Algorithm to Enumerate All Cutsets of a Graph in Linear Time per Cutset

Abstract: Thts paper deals wRh the problem of enumerating all the cutsets or all the s-t cutsets separatmg two spectfied verttces s and t m an undirected graph A vanety of approaches have been proposed for this problem, among which one based on the partmon era set of veruces rote two sets is the most effi¢ienL It is first shown that an algorithm of this type has time complexity O((n + m)(n -log2#)#), and two new algorithms with ume complexity O((n + m)O + I)) are then proposed One of these new algorithms has space compl… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
35
0
1

Year Published

1986
1986
2014
2014

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 83 publications
(37 citation statements)
references
References 7 publications
1
35
0
1
Order By: Relevance
“…In this section we present a technique which is a variant of the so called supergraph approach that has been used in the literature for instance, to generate all minimal feedback vertex and arc sets [13], minimal s-t cuts [16], minimal spanning trees [14], and minimal blockers of perfect matchings in bipartite graphs [3]. To explain the method briefly, a supergraph is a strongly connected directed graph G whose vertices are the objects that we would like to generate.…”
Section: Generating Minimal Transversals Of a Hypergraphmentioning
confidence: 99%
See 1 more Smart Citation
“…In this section we present a technique which is a variant of the so called supergraph approach that has been used in the literature for instance, to generate all minimal feedback vertex and arc sets [13], minimal s-t cuts [16], minimal spanning trees [14], and minimal blockers of perfect matchings in bipartite graphs [3]. To explain the method briefly, a supergraph is a strongly connected directed graph G whose vertices are the objects that we would like to generate.…”
Section: Generating Minimal Transversals Of a Hypergraphmentioning
confidence: 99%
“…Given a graph G = (V , E) and two vertices s, t ∈ V , the two-terminal cut generation problem calls for listing all minimal subsets of edges whose removal disconnects s and t. This problem is known to be solvable in O(Nm + m + n) time and O(n + m) space [16], where n and m are the numbers of vertices and edges in the input graph, and N is the total number of cuts. In this paper, we study the following natural extension of this problem: Note that for i = j , s i and s j , or s i and t j , or t i and t j may coincide.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, we seek to provide a more direct means to determine where perturbation of the probability of transitions between states leads to large system performance degradations. To do this, we leverage previous work on minimal s-t cut set identification [32][33][34][35] described below. Minimal cut set identification methods have long been used for analysis of VLSI designs, network systems, and design of various other distributed systems.…”
Section: Previous Workmentioning
confidence: 99%
“…By reducing the transition probability values of these common transitions to 0, the flow of tasks to the Tasks Completed state is also reduced to 0. In discrete mathematics, a set of one or more edges, which if removed, disconnects all paths between two vertices s and t is often referred to as an s-t cut set, as for example [32]. An s-t cut set is defined to be a minimal s-t cut set if removal of any edge from the cut set causes s and t to be reconnected.…”
Section: Finding State Transition That Disconnect Paths To Absorbing mentioning
confidence: 99%
“…This problem, for example, has an application in network reliability, see Colbourn [4]. Abel and Bicker [1], Bellmore and Jensen [3] and Tsukiyama et al [6] In this paper, we propose a generalized framework and discuss its application.…”
Section: Introductionmentioning
confidence: 99%