Predictive/reactive Scheduling with Uncertain Disruptions

نویسندگان

  • Liping Zhang
  • Xinyu Li
  • Liang Gao
  • Yang Yang
  • Ping Jiang
چکیده

In most real production environment, schedules are usually inevitable with the presence of a variety of unexpected disruptions. Thus it is necessary to develop predictive/reactive schedules which can absorb disruptions while maintaining high shop performance. In this paper, a robust predictive/reactive scheduling method is developed for solving job shop scheduling in dynamic environment. It contains two respects: Firstly, a hybrid algorithm for rescheduling the affected operations in a job shop is presented. Secondly, the additional idle time is inserted into the schedule to absorb the impacts of unexpected disruptions. A designed experiment is performed on job shop scheduling problems to study the effect of the proposed scheduling method in different disruptions scenarios. The performance of the proposed scheduling methods, with respect to measures of efficiency and stability, has compared with that of Total rescheduling Right-Shift rescheduling and Affected operations rescheduling without additional idle time. The results demonstrate that the proposed scheduling method outperforms among these rescheduling methods, and it provides high predictability for solving the job shop scheduling with uncertain disruptions.

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تاریخ انتشار 2011