Proposition of New Genetic Operator for Solving Joint Production and Maintenance Scheduling : Application to the Flow Shop Problem.

Fatima Benbouzid-Sitayeb (1) , Christophe Varnier (2) , Nourredine Zerhouni (2)

1 LMCS - Laboratoire de Méthodes de Conception de Systèmes
2 LAB - Laboratoire d'automatique de Besançon

Genetic algorithms are used in scheduling leading to efficient heuristic methods for large sized problems. The efficiency of a GA based heuristic is closely related to the quality of the used GA scheme and the GA operators: mutation, selection and crossover. In this paper, we propose a Joint Genetic Algorithm (JGA), for joint production and maintenance scheduling problem in permutation flowshop, in which different genetic joint operators are used. We also proposed a joint structure to represent an individual in with two fields: the first one for production data and the second one for maintenance data. We used different Taillard benchmarks to compare the performances of JGA with each proposed operator.

Mots clés: joint mutation; GA; production; maintenance; joint scheduling; joint crossover; joint mutation.

Domaines: Automatique / Robotique

Fatima Benbouzid-Sitayeb, Christophe Varnier, Nourredine Zerhouni. Proposition of New Genetic Operator for Solving Joint Production and Maintenance Scheduling : Application to the Flow Shop Problem.. IEEE International Conference Service System and Service Management, ICSSSM'06., Oct 2006, Troyes, France. pp.607-613, ⟨10.1109/ICSSSM.2006.320531⟩. ⟨hal-00334160⟩