Genetic algorithms for the flow shop scheduling problem with availability constraints

Most of the papers on scheduling take the common assumption that the machines are always available. We consider a flow shop problem with availability constraints (FSPAC), in which unavailability times of the machines are known in advance as a preventive maintenance activity. Contrary to the majority of previous works, preemption of tasks is not allowed. Two approaches are considered to deal with the maintenance activity: either the maintenance tasks are totally fixed or the location of some of them is optimized. As the problem is NP-hard, a genetic algorithm approach is proposed to solve the makespan and the total weighted tardiness minimization problems. Numerical experiments are presented to test the efficiency of the approach.