Reduced RLT constraints for polynomial programming

Sonia Cafieri (1) , Pierre Hansen (2) , Lucas Létocart (3) , Leo Liberti (4) , Frédéric Messine (5)

1 ENAC - Ecole Nationale de l'Aviation Civile
2 HEC Montréal - HEC Montréal
3 LIPN - Laboratoire d'Informatique de Paris-Nord
4 LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
5 ENSEEIHT - Ecole Nationale Supérieure d'Electrotechnique, d'Electronique, d'Informatique, d'Hydraulique et de Télécommunications

An extension of the reduced Reformulation-Linearization Technique constraints from quadratic to general polynomial programming problems with linear equality constraints is presented and a strategy to improve the associated convex relaxation is proposed.

Mots clés: polynomial; MINLP; sBB; convex relaxation; RLT

Domaines: Mathématiques [math]; Optimisation et contrôle [math.OC]

Sonia Cafieri, Pierre Hansen, Lucas Létocart, Leo Liberti, Frédéric Messine. Reduced RLT constraints for polynomial programming. EWMINLP10, European Workshop on Mixed Integer Nonlinear Programming, Apr 2010, Marseille, France. pp 205-207. ⟨hal-00938438⟩