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Algorithmica
Article . 2000 . Peer-reviewed
License: Springer TDM
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Finding Edge-Disjoint Paths in Partial k -Trees

Finding edge-disjoint paths in partial \(k\)-trees
Authors: Takao Nishizeki; Xiao Zhou; Syurei Tamura;

Finding Edge-Disjoint Paths in Partial k -Trees

Abstract

For a given graph \(G\) and \(p\) pairs \((s_i,t_i)\), \(1\leq i\leq p\), of vertices of \(G\), the edge-disjoint paths problem is to find \(p\) pairwise edge-disjoint paths \(P_i\), \(1\leq i \leq p\), connecting \(s_i\) and \(t_i\). This paper gives two algorithms for the edge-disjoint paths problem on partial \(k\)-trees. The first one solves the problem for any partial \(k\)-tree \(G\) and runs in polynomial time if \(p=O(\log n)\) and in linear time if \(p=O(1)\), where \(n\) is the number of vertices in \(G\). The second one solves the problem under some restrictions on the location of terminal pairs even if \(p\geq \log n\).

Related Organizations
Keywords

Graph theory (including graph drawing) in computer science, treewidth, edge-coloring, edge-disjoint paths, Nonnumerical algorithms, partial \(k\)-tree

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Average
Top 10%
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