A memetic algorithm for solving permutation flow shop problems with known and unknown machine breakdowns

The Permutation Flow Shop Scheduling Problem (PFSP) is considered to be one of the complex combinatorial optimization problems. For PFSPs, the schedule is produced under ideal conditions that usually ignore any type of process interruption. In practice, the production process is interrupted due to many different reasons, such as machine unavailability and breakdowns. In this paper, we propose a Genetic Algorithm (GA) based approach to deal with process interruptions at different points in time in Permutation Shop Floor scenarios. We have considered two types of process interruption events. The first one is predictive, where the interruption information is known well in advance, and the second one is reactive, where the interruption information is not known until the breakdown occurs. An extensive set of experiments has been carried out, which demonstrate the usefulness of the proposed approach.