An efficient and safe framework for solving optimization problems

Yahia Lebbah (1, 2) , Claude Michel (1) , Michel Rueher (1)

1 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe CEP
2 Département d'Informatique [Oran]

Interval methods have shown their ability to locate and prove the existence of a global optima in a safe and rigorous way. Unfortunately, these methods are rather slow. Efficient solvers for optimization problems are based on linear relaxations. However, the latter are unsafe, and thus may overestimate, or, worst, underestimate the very global minima. This paper introduces QuadOpt, an efficient and safe framework to rigorously bound the global optima as well as its location. QuadOpt uses consistency techniques to speed up the initial convergence of the interval narrowing algorithms. A lower bound is computed on a linear relaxation of the constraint system and the objective function. All these computations are based on a safe and rigorous implementation of linear programming techniques. First experimental results are very promising.

Mots clés: Global optimization; Safe linear relaxations; Constraint programming

Domaines: Intelligence artificielle [cs.AI]; Algorithme et structure de données [cs.DS]; Analyse numérique [cs.NA]

Yahia Lebbah, Claude Michel, Michel Rueher. An efficient and safe framework for solving optimization problems. Journal of Computational and Applied Mathematics, 2007, 199, pp.372-377,. ⟨10.1016/j.cam.2005.08.037⟩. ⟨hal-00510304⟩