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.
Cite
@article{arxiv.0807.2382,
title = {Revisiting the upper bounding process in a safe Branch and Bound algorithm},
author = {Alexandre Goldsztejn and Yahia Lebbah and Claude Michel and Michel Rueher},
journal= {arXiv preprint arXiv:0807.2382},
year = {2008}
}
Comments
Optimization, continuous domains, nonlinear constraint problems, safe constraint based approaches; 14th International Conference on Principles and Practice of Constraint Programming, Sydney : Australie (2008)