Improving the linear relaxation of maximum k-cut with semidefinite-based constraints
We consider the maximum k-cut problem that involves partitioning the vertex set of a graph into k subsets such that the sum of the weights of the edges joining vertices in different subsets is maximized. The associated semidefinite programming (SDP) relaxation is known to provide strong bounds, but...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Elsevier
2019
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/e83f83c8eb1e402f83fc6eed4310cd7b |
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