ANALYSIS OF PERIODIC AND EVENT-DRIVEN RESCHEDULING POLICIES IN DYNAMIC SHOPS

We address the problem of rescheduling production systems in the face of dynamic job arrivals. Using simple single- and parallel-machine models to gain insight, we provide worst-case and computational analyses of periodic and event-driven rescheduling policies. Our results indicate that event-driven policies can obtain high-quality schedules with less rescheduling than continuous rescheduling policies. We also show that if structure in the job arrival process is exploited very effective periodic rescheduling policies can be designed.