Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring
We present practical algorithms for constructing partitions of graphs into a fixed number of vertex-disjoint subgraphs that satisfy particular degree constraints. We use this in particular to find k-cuts of graphs of maximum degree ∆ that cut at least a k - 1/k (1 + 1/2∆+k-1 ) fraction of the edges,...
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sg-smu-ink.sis_research-11722016-12-14T02:47:44Z Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring Halldorsson, Magnus M. Lau, Hoong Chuin We present practical algorithms for constructing partitions of graphs into a fixed number of vertex-disjoint subgraphs that satisfy particular degree constraints. We use this in particular to find k-cuts of graphs of maximum degree ∆ that cut at least a k - 1/k (1 + 1/2∆+k-1 ) fraction of the edges, improving previous bounds known. The partitions also apply to constraint networks, for which we give a tight analysis of natural local search heuristics for the maximum constraint satisfaction problem. These partitions also imply efficient approximations for several problems on weighted bounded-degree graphs. In particular, we improve the best performance ratio for the weighted independent set problem to 3/∆+2 , and obtain an efficient algorithm for coloring 3-colorable graphs with at most 3∆+2/4 colors. 1997-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/173 info:doi/10.7155/jgaa.00003 https://ink.library.smu.edu.sg/context/sis_research/article/1172/viewcontent/LauC1997LowDegree_Graph.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Numerical Analysis and Scientific Computing |
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Numerical Analysis and Scientific Computing Halldorsson, Magnus M. Lau, Hoong Chuin Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
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We present practical algorithms for constructing partitions of graphs into a fixed number of vertex-disjoint subgraphs that satisfy particular degree constraints. We use this in particular to find k-cuts of graphs of maximum degree ∆ that cut at least a k - 1/k (1 + 1/2∆+k-1 ) fraction of the edges, improving previous bounds known. The partitions also apply to constraint networks, for which we give a tight analysis of natural local search heuristics for the maximum constraint satisfaction problem. These partitions also imply efficient approximations for several problems on weighted bounded-degree graphs. In particular, we improve the best performance ratio for the weighted independent set problem to 3/∆+2 , and obtain an efficient algorithm for coloring 3-colorable graphs with at most 3∆+2/4 colors. |
format |
text |
author |
Halldorsson, Magnus M. Lau, Hoong Chuin |
author_facet |
Halldorsson, Magnus M. Lau, Hoong Chuin |
author_sort |
Halldorsson, Magnus M. |
title |
Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
title_short |
Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
title_full |
Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
title_fullStr |
Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
title_full_unstemmed |
Low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
title_sort |
low-degree graph partitioning via local search with applications to constraint satisfaction, max cut, and coloring |
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Institutional Knowledge at Singapore Management University |
publishDate |
1997 |
url |
https://ink.library.smu.edu.sg/sis_research/173 https://ink.library.smu.edu.sg/context/sis_research/article/1172/viewcontent/LauC1997LowDegree_Graph.pdf |
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1770568910126448640 |