We study a pallet building problem that originates from a case study at a company that produces pallet building robotized systems. The problem takes into account well known constraints, such as rotation and stackability, and we introduce two practical constraints named visibility and contiguity between items of the same type. We formalize the problem and propose heuristic algorithms to solve it, using a strategy that first creates 2D layers and, then, creates the final 3D pallets. The proposed heuristic is based mainly on the Extreme Points heuristic, that is tailored to choose feasible positions to pack items during the construction of the solution. Besides that, we adapt our proposed heuristic using other basic heuristics from the literature, considering different constraints. The performance of the algorithms is assessed through extensive computational tests on real-world instances, and the obtained results show the proposed heuristics are able to create compact packing in a very short time.
Solution of a practical pallet building problem with visibility and contiguity constraints / Iori, M.; Locatelli, M.; Moreira, M. C. O.; Silveira, T.. - 1:(2020), pp. 327-338. (Intervento presentato al convegno 22nd International Conference on Enterprise Information Systems, ICEIS 2020 tenutosi a Prague nel 2020) [10.5220/0009351703270338].
Solution of a practical pallet building problem with visibility and contiguity constraints
Iori M.;Locatelli M.;
2020
Abstract
We study a pallet building problem that originates from a case study at a company that produces pallet building robotized systems. The problem takes into account well known constraints, such as rotation and stackability, and we introduce two practical constraints named visibility and contiguity between items of the same type. We formalize the problem and propose heuristic algorithms to solve it, using a strategy that first creates 2D layers and, then, creates the final 3D pallets. The proposed heuristic is based mainly on the Extreme Points heuristic, that is tailored to choose feasible positions to pack items during the construction of the solution. Besides that, we adapt our proposed heuristic using other basic heuristics from the literature, considering different constraints. The performance of the algorithms is assessed through extensive computational tests on real-world instances, and the obtained results show the proposed heuristics are able to create compact packing in a very short time.
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