Local rescheduling - A novel approach for efficient response to schedule disruptions

Whenever an unforeseen disturbance occurs during the execution of scheduled operations, rescheduling might be necessary: Beside temporal shifts and the allocation of alternative resources, also potential switches from one process variant to another one have typically to be considered. In realistic scenarios of operational disruption management (DM) the high number of potential options makes the provision of online decision support complex. It is thus necessary to significantly reduce the size of the regarded (search) problems which can for instance be achieved by applying methods of partial rescheduling. However, existing approaches such as Affected Operations Rescheduling (AOR) or Matchup Scheduling (MUP) focus on production-specific problems and can not be applied to more generic problem classes. To overcome this limitation, we introduce a novel approach to partial rescheduling in this paper: Local Rescheduling (LRS) is based on the incremental extension of a time window which is regarded for potential schedule modifications. We discuss how this time window can be initialized, extended and used for rescheduling. Moreover, we illustrate the superior performance of LRS in comparison with full rescheduling and MUP.