A Genetic Algorithm for Flow-Shop Scheduling Problems with Multiprocessor Tasks

We propose a Genetic Algorithm for scheduling multiprocessor tasks in multi-stage flow-shop environments. We present two special crossover operators that we developed for this particular problem, together with the implementation of mutation operators as well as a partial reshuffling procedure. We conclude with the results of our computational experiments.