Publication | Closed Access
A hybrid meta-heuristic algorithm for flowshop robust scheduling under machine breakdown uncertainty
26
Citations
17
References
2016
Year
Mathematical ProgrammingEngineeringSmart ManufacturingHybrid Meta-heuristic AlgorithmOptimal System DesignOperations ResearchUncertainty QuantificationSystems EngineeringCombinatorial OptimizationMachine Breakdown UncertaintyRobust OptimizationPreventive MaintenanceComputer EngineeringManufacturing PlanningManufacturing SystemsScheduling (Computing)Computer ScienceInteger ProgrammingScheduling ProblemProduction SchedulingScheduling (Production Processes)Permanent Availability
One of the most important assumptions in production scheduling is permanent availability of the machines without any breakdown. In real-world scheduling problems, machines could be unavailable due to various reasons such as preventive maintenance and unpredicted breakdowns. In this paper, a flowshop scheduling problem under machine breakdown uncertainty is studied. The machines are subject to breakdown in practice caused by components’ wear-out. A proactive scheduling is considered to deal with unpredictable machine breakdown. An effective hybrid meta-heuristic algorithm based on genetic and simulated annealing algorithms is proposed to tackle such an NP-hard problem. To evaluate the performance of the proposed algorithm, its performance in terms of maximising the β-robustness of makespan was compared with six other heuristic and meta-heuristic algorithms. Computational results confirm that the proposed algorithm outperforms the others.
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