Dynamic Scheduling in Multiproduct Batch Plants

Abstract

This work introduces a novel MILP formulation for reactive scheduling of multiproduct batch plants to optimally generate updated schedules due to the occurrence of unforeseen events. It can also be used to improve a non-optimal production schedule before it is executed. The approach is based on a continuous-time problem representation that takes into account the schedule in progress, the updated information on the batches still to be processed, the present plant state and the time data. To limit the changes on the current schedule, rescheduling operations involving local reordering and unit reallocation of old batches as well as the insertion of new batches are just permitted. In contrast to previous contributions, multiple rescheduling operations can be performed at the same time. The MILP problem formulation is iteratively solved until no further improvement on the current schedule is obtained. Three large-size example problems were successfully solved with low computational cost.