Improved solutions for the freight consolidation and containerization problem using aggregation and symmetry breaking

We consider the freight consolidation and containerization problem, which consists of loading items into containers and then shipping these containers to different warehouses from where they are delivered to their final destinations. We show through computational experiments that very good solutions can be obtained by heuristically aggregating the items and then using MIP approaches to deal with the aggregated problem. We have been able to find a solution as good as the best known in the literature for 100% of the instances with small items, encountering strictly better solutions for 40.6% of them. Our approach found solutions as good as the best known in the literature for 88.9% of the instances with large items, obtaining strictly better in 59.4% of the cases.