A rolling horizon heuristic for reactive scheduling of batch process operations

Batch chemical plants are dynamic processing facilities where static production schedules can rarely be adhered to due to market and operating uncertainties. On-line schedule modifications of a priori timing assignments and resource allocations in response to unantipicated disruptions is done through a decomposition heuristic that uses a rolling horizon implementation policy. An attempt is made to minimize the impact of the disruptions on the original schedule near the point of each deviation while exploiting the combinatorial flexibility of task and resource reassignments in future scheduling time windows. The problem is addressed as a multiobjective optimization problem involving completion time criteria, relative customer importance, and production cost considerations. A rigorous analysis of problem sensitive parameters, including penalty weights and subhorizon length, is conducted. A model plant case study is performed. Variations on storage availability and task flexibility are investigated in an attempt to characterize dominant effects of the weighting parameters. Results indicate that user preference can serve as a strong guide for obtaining near optimal reactive scheduling solutions. It is shown that the combinatories can be controlled and that costly and inefficient full scale resheduling of multipurpose production facilities can be avoided.