Integrated Optimization Of Production Scheduling And Preventive Maintenance On Parallel Machines

As production scheduling is one of the key factors that affects themanufacturing system performance, a great amount of productionscheduling models have been studied and designed to solve this problem.However, previous theoretical researches always assume machines arealways available for manufacturing and do not take the effect of machineunavailability into account. Therefore, these assumptions are inappropriatein real manufacturing. Considering the machine unavailability, this paper isdevoted to propose an integrated study of production scheduling andpreventive maintenance planning on parallel machines.This paper proposes a mixed integer programming model to minimizethe makespan (Cm ax) under the assumption that preventive maintenancewill be taken under periodic flexible time window. This paper proves thelow bound of this problem and proposed a heuristic algorithm named FLBto solve this problem. Data testing proves the efficiency and correctness ofthis algorithm.Considering the corrective maintenance caused by stochasticbreakdowns, this paper propose a multi-objective programming model inorder to find a compromised solution to minimize the makespan () for the production part and the average cost (c) for the maintenance side. Arevised genetic algorithm (GA) is proposed to solve this problem, and iscompared with numerical algorithm to show its efficiency and accuracy.The comparison with separated decision-making model shows that theintegrated decision-making model can better solve this problem.