A Milp Reactive Scheduling Framework for Resource-constrained Multistage Batch Facilities

This work introduces a MILP reactive scheduling framework for resource-constrained multistage batch facilities with multiple parallel units at each stage. The approach is based on a continuous time domain representation that takes into account the schedule currently in progress, the updated information on the old production orders still to be processed, new order arrivals, the present plant state and the limited availability of renewable discrete resources like processing units and manpower. Order due dates and sequence-dependent changeovers can also be considered. The proposed technique is able to generate updated schedules when unforeseen events like deviations in processing times, equipment breakdown or batch reprocessing occur. To avoid full-scale rescheduling, the approach just allows schedule modifications involving starting time shifting, limited resource reallocation and local batch reordering at any discrete resource. The rescheduling algorithm is iteratively performed to restore feasibility at minimum increase of the objective function. Performance measures like make-span or average order lateness can be used. A large-scale case study was successfully solved at low computational time.