Genetic Algorithms for the Flow Shop Scheduling Problem with availability constraints
Abstract
Most of the papers on scheduling take the common assumption that the machines are always available. In this paper, 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.