Coauthor: Philipp Baumann

We investigate short-term scheduling of industrial make-and-pack production processes. The planning problem consists of minimizing the production makespan while meeting given end-product demands. A large number of operations, sequence-dependent changeover times, multi-purpose storage units with finite capacities, batch splitting, quarantine times, partial equipment connectivity, and material transfer times render the problem a challenging task. Known MILP formulations for such production processes can solve only small and medium-sized problem instances in reasonable CPU times. We present a hybrid heuristic approach to tackle large-scale instances. Under this approach, the set of batches is divided into several subsets, which are then scheduled iteratively using a MILP model. We enhance the performance of the heuristic by eliminating redundant constraints and variables after each iteration. The applicability of the proposed heuristic is demonstrated by means of a real-world production process.