The NP-hard scheduling problems of semiconductor manufacturing systems(SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme...The NP-hard scheduling problems of semiconductor manufacturing systems(SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance(such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule(SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.展开更多
基金funded by the National Natural Science Foundation of China(Grant NO:71690234)
文摘The NP-hard scheduling problems of semiconductor manufacturing systems(SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance(such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule(SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.
