Revisiting the upper bounding process in a safe Branch and Bound algorithm

Abstract : Finding feasible points for which the proof succeeds is a critical issue in safe Branch and Bound algorithms which handle continuous problems. In this paper, we introduce a new strategy to compute very accurate approximations of feasible points. This strategy takes advantage of the Newton method for under-constrained systems of equations and inequalities. More precisely, it exploits the optimal solution of a linear relaxation of the problem to compute efficiently a promising upper bound. First experiments on the Coconuts benchmarks demonstrate that this approach is very effective.
Type de document :
Communication dans un congrès
P.J. Stuckey. 14th International Conference on Principles and Practice of Constraint Programming, Sep 2008, Sydney, Australia. LNCS (5202), pp.598-602, 2008
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Contributeur : Michel Rueher <>
Soumis le : mardi 15 juillet 2008 - 13:53:34
Dernière modification le : lundi 21 mars 2016 - 17:50:40
Document(s) archivé(s) le : vendredi 28 mai 2010 - 20:59:50

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  • HAL Id : hal-00297086, version 1
  • ARXIV : 0807.2382

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Alexandre Goldsztejn, Yahia Lebbah, Claude Michel, Michel Rueher. Revisiting the upper bounding process in a safe Branch and Bound algorithm. P.J. Stuckey. 14th International Conference on Principles and Practice of Constraint Programming, Sep 2008, Sydney, Australia. LNCS (5202), pp.598-602, 2008. <hal-00297086>

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