Industrial multi-resource flexible job shop scheduling with partially necessary resources

This paper is dedicated to the study of industrial extensions of the flexible job shop scheduling problem with multiple resources in order to propose an alternative to expensive optimization software for small to medium-sized manufacturing companies. In this context, we propose a generic model able to tackle some constraints often found in industrial scheduling problems. This model tackles partially necessary resources by decomposing operations into stages. Instances are solved by a simulated annealing metaheuristic which is further improved using efficient conditions to filter non-interesting solutions. We compare our approach to a constraint programming model using a commercial solver. Extensive experiments and statistical analysis show that our method is competitive and of practical use in the industrial context.