Minimizing expected makespan in flowshop with on condition based maintenance constraint by integrating heuristics and simulation

The availability of the machine is one of the most important assumptions on many scheduling problems under any situation. However, in most actual life manufacturing settings a machine can be unavailable for many reasons, such as unforeseen scheduled preventive. In this paper, we study scheduling flowshops problem under ’condition based’ maintenance constraints to minimize the expected makespan using simulation to tackle the randomness of the problem at hand. Heuristics and meta hueristics is used to tackle such an NP-hard problem. It is additionally supposed that machines suffer form degradation due to shocks, thus preventive maintenance should be done on machines. Furthermore, it is assumed that the degradation value of machine is known at inspection time. Overall, three adaptations of existing metaheuristic and hueristics methods are evaluated for the integration of preventive maintenance and they are applied to a set of 1080 instances. The preliminary results manifest the superiority of genetic algorithm over others.