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In this paper, we propose a dynamic scheduling method for production systems with processing time uncertainty. Dynamic scheduling problems are assumed to be a series of staticproblems and scheduled on a rolling basis. The proposed scheduling method consists of two phases : off-line optimization and real-time execution. The off-line optimization for each static problem is carried out using the mixture of a genetic algorithm and a priority rule. In the genetic algorithm, genes, each of which is assigned to each operation of jobs, and priorities calculated by the priority rule are used for off-line optimization. In the real-time execution phase, real-time scheduling is carried out using the priority rule applied in real-time and the genes obtained in the off-line optimization. This proposed method is considered as the mixture of off-line periodic optimization andreal-time scheduling. Numerical experiments show that the proposed method is effective underthe intermediate conditions of the diametrically opposite ones in which real-time scheduling oroff-line scheduling is effective.

Dynamic Scheduling with Processing Time Uncertainty Using the Mixture of Periodic Optimization and Real-time Scheduling