Extraction de règles d'ordonnancement : Aide au paramétrage d'un progiciel d'ordonnancement.

Brigitte Chebel-Morello (1) , Pierre Baptiste (2) , Emmanuel Lereno (1)

1 LAB - Laboratoire d'automatique de Besançon
2 Département de Mathématiques et de Génie Industriel. - Département de Mathématiques et de Génie Industriel.

Conditions complexity of management workshop of production manufacturing increases and requires heuristic algorithm adapted to the context. The principal difficulty then lies in the choice of heuristic algorithm to apply. We propose a help method to schedule, and more specifically a parameter setting up's help of an industrial scheduling software, being based on machine learning system able to extract knowledge from data. An inductive learning based on examples system is developed and replaced in a process of ECD (Extraction of Knowledge starting from Data). The first step pf this process is specific to our problem and uses in this case the capacities of simulation of a market software of scheduling.

Mots clés: software package; filtering; computer simulation; heuristic method; scheduling; extraction process; filter; behavioral analysis; knowledge extraction; knowledge discovery; inductive logic programming; inductive learning; learning systems; educational software program; learning (artificial inelligence); artificial intelligence; production management; software package.

Domaines: Automatique / Robotique

Brigitte Chebel-Morello, Pierre Baptiste, Emmanuel Lereno. Extraction de règles d'ordonnancement : Aide au paramétrage d'un progiciel d'ordonnancement.. Journal Européen des Systèmes Automatisés (JESA), 2006, 40 (1), pp.11-32. ⟨hal-00327337⟩