Exploiting Semidefinite Relaxations in Constraint Programming

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dc.creatorvan Hoeve, Willem Jan
dc.date2004-07-16
dc.date.accessioned2026-07-07T03:21:34Z
dc.date.available2026-07-07T03:21:34Z
dc.descriptionConstraint programming uses enumeration and search tree pruning to solve combinatorial optimization problems. In order to speed up this solution process, we investigate the use of semidefinite relaxations within constraint programming. In principle, we use the solution of a semidefinite relaxation to guide the traversal of the search tree, using a limited discrepancy search strategy. Furthermore, a semidefinite relaxation produces a bound for the solution value, which is used to prune parts of the search tree. Experimental results on stable set and maximum clique problem instances show that constraint programming can indeed greatly benefit from semidefinite relaxations.
dc.description18 pages, 4 figures. Submitted preprint
dc.identifierhttps://arxiv.org/abs/cs/0407041
dc.identifierhttp://arxiv.org/abs/cs/0407041
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32250
dc.subjectDiscrete Mathematics
dc.subjectProgramming Languages
dc.subjectG.1.6; G.2.2; D.3.3
dc.titleExploiting Semidefinite Relaxations in Constraint Programming
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