Multiobjective Optimization Approach to Solve a Maintenance Process Problem
Résumé
In this paper, a multiobjective optimization study of maintenance process is
developed. The considered problem is inspired by a real case. Given the complexity of
the industrial case, we combined a discrete event simulation model with an optimization
engine based on non-dominated sorting genetic algorithm II (NSGA-II). The coupling is
used in order to optimize the performances of the simulation model by choosing the best
queues’ scheduling policy. The issue is to reorganize the maintenance process under
operator’s qualifications and interventions emergency degree. The NSGA-II engine and
simulation model operate in parallel over time with interactions. After computation, we
obtain high quality solutions in very short commuting time.