Evaluating periodic rescheduling policies using a rolling horizon framework in an industrial-scale multipurpose plant

Abstract

Periodic rescheduling is a commonly used method for scheduling short-term operations. Through computational experiments that vary plant parameters, such as the load and the capacity of a facility, we investigate the effects these parameters have on plant performance under periodic rescheduling. The results show that choosing a suitable rescheduling policy depends highly on some key plant parameters. In particular, by modifying various parameters of the facility, the performance ranking of the various rescheduling policies may be reversed compared to the results obtained with nominal parameter values. This highlights the need to consider both facility characteristics and what the crucial objective of the facility is when selecting a rescheduling policy. This study considers a variant of the job shop problem, used to model the operation of an industrial-scale analytical services facility using different periodic rescheduling policies. A rolling horizon routine is used to schedule operations over the scheduling horizon. Performance is measured in terms of job throughput, job makespan, and proportion of jobs on time at the end of the scheduling horizon to obtain a more complete understanding of how performance varies between rescheduling policies.