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Exploiting Semidefinite Relaxations in Constraint Programming

2004/07/16 by Willem Jan van Hoeve, van Hoeve, Willem Jan
Computer Science · #Constraint Satisfaction and Optimization #D.3.3 #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #G.1.6 #G.2.2 #Programming Languages (cs.PL) #cs.DM #cs.PL

paper · pdf · doi:10.48550/arxiv.cs/0407041

18 pages, 4 figures. Submitted preprint

arxiv created 2004/07/16 · openalex publication_date 2004/07/16 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Constraint 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.

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