Optimisation par hybridation d'un CSP avec un algorithme génétique

Nicolas Barnier (1) , Pascal Brisset (2)

1 MAIA-OPTIM - ENAC Equipe MAIAA-OPTIM
2 ENAC - Ecole Nationale de l'Aviation Civile

Within the framework of Constraint Logic Programming on finite domains CLP(FD), we introduce a new optimization method based on a Genetic Algorithm. The main idea is the handling of sub-domains of the CSP variables by the genetic algorithm. The population of the genetic algorithm is made up of strings of sub-domains whose fitness are computed through the resolution of the corresponding sub-CSPs which are somehow much easier than the original problem. We provide basic and dedicated recombination and mutation operators with various degrees of robustness. The first set of experimentations adresses a naïve formulation of the Vehicle Routing Problem (VRP) and the Radio Link Frequency Assignement Problem (RLFAP). The results are quite encouraging as we outperform CLP(FD) techniques and genetic algorithm alone.

Mots clés: optimisation; genetic algorithm; constraint programming; CPS; algorithme génétique; méthode mixte

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

Nicolas Barnier, Pascal Brisset. Optimisation par hybridation d'un CSP avec un algorithme génétique. JFPLC 97, 6èmes Journées Francophones de Programmation Logique et Programmation par Contraintes, May 1997, Orléans, France. pp xxxx. ⟨hal-00937703⟩