Spanning Distribution Trees of Graphs
Masaki Kawabata,Takao Nishizeki +1 more
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In this article, the authors show that the problem is NP-complete even for series-parallel graphs, and give a pseudo-polynomial time algorithm to solve the problem for a given seriesparallel graph G.Abstract:
Let G be a graph with a single source w, assigned a positive integer called the supply. Every vertex other than w is a sink, assigned a nonnegative integer called the demand. Every edge is assigned a positive integer called the capacity. Then a spanning tree T of G is called a spanning distribution tree if the capacity constraint holds when, for every sink v, an amount of flow, equal to the demand of v, is sent from w to v along the path in T between them. The spanning distribution tree problem asks whether a given graph has a spanning distribution tree or not. In the paper, we first observe that the problem is NP-complete even for series-parallel graphs, and then give a pseudo-polynomial time algorithm to solve the problem for a given series-parallel graph G.read more
Citations
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Journal ArticleDOI
An ant colony optimization algorithm for partitioning graphs with supply and demand
TL;DR: The tests show that the proposed ant colony optimization algorithm for the problem of maximum partitioning of graphs with supply and demand has an average relative error of less than 0.5% when compared to known optimal solutions.
Journal ArticleDOI
A mixed integer program for partitioning graphs with supply and demand emphasizing sparse graphs
TL;DR: The conducted computational experiments have shown that the proposed MIP formulation, developed for the problem of maximal partitioning of graphs with supply and demand (MPGSD) for arbitrary graphs, is especially suitable for sparse graphs.
Spanning Distribution Forests of Graphs (Extended Abstract)
Keisuke Inoue,Takao Nishizeki +1 more
TL;DR: In this article, the authors present a pseudo-polynomial time algorithm to find a spanning distribution forest of a given series-parallel graph, and then extend the algorithm for graphs with bounded tree-width.
Book ChapterDOI
Spanning Distribution Forests of Graphs
Keisuke Inoue,Takao Nishizeki +1 more
TL;DR: A pseudo-polynomial time algorithm to find a spanning distribution forest of a given series-parallel graph, and then extend the algorithm for graphs with bounded tree-width is presented.
Proceedings ArticleDOI
A Mixed Integer Program for the Spanning Distribution Forest of a Power Network
TL;DR: In this work, a mixed integer program (MIP) is developed for finding optimal solutions for the SDFPN and a greedy constructive algorithm is designed for finding feasible solutions for large problem instances at low computational costs.
References
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Linear-time computability of combinatorial problems on series-parallel graphs
TL;DR: It is shown in a umfied manner that there exist hnearume algorithms for many combinatorial problems ff an input graph is restricted to the class of series-parallel graphs.
Journal ArticleDOI
Computers and Intractability: A Guide to the Theory of NP-Completeness (Michael R. Garey and David S. Johnson)
Journal ArticleDOI
An efficient brute-force solution to the network reconfiguration problem
A.B. Morton,Iven Mareels +1 more
TL;DR: In this paper, a method for determining a minimal-loss radial configuration for a power distribution network, using an exhaustive search algorithm, is proposed, deriving its efficiency from the use of graph-theoretic techniques involving semi-sparse transformations of a current sensitivity matrix.
Proceedings ArticleDOI
Single-source unsplittable flow
TL;DR: In this paper, the authors considered the problem of single-source disjoint path selection in directed and undirected graphs, and provided constant factor approximation algorithms for three natural optimization versions of this problem.
Journal ArticleDOI
On the single-source unsplittable flow problem
TL;DR: The necessary cut condition is satisfied and it is shown how to compute an unsplittable flow satisfying the demands such that the total flow through any edge exceeds its capacity by at most the maximum demand.