We consider a complex real-world problem in slab yard management that deals with block relocation and slab stack shuffling in a single problem. For this integrated problem, we designed a two-level metaheuristic approach with a local search procedure that works at the level of the slab selections and uses an inner greedy heuristic for deciding relocations and retrievals. We tested our solution approach on a novel dataset using an actual yard layout and a simulation tool to set its initial configuration. Our search method successfully obtained high-quality solutions, even for large instances involving over 2000 slabs. To assess the performance of our search method compared to state-of-the-art ones, we adapted it to a simpler formulation from recent literature and tested it on public benchmarks. Our method proved as good as the best existing ones in most available instances and consistently outperformed them on the largest ones.
