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arXiv · 0807.2382

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

Alexandre Goldsztejn·Yahia Lebbah·Claude Michel·Michel Rueher
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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.

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Alexandre Goldsztejn, Yahia Lebbah, Claude Michel, Michel Rueher. 2008-07-15. Revisiting the upper bounding process in a safe Branch and Bound algorithm. https://arxiv.org/abs/0807.2382

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