Article ID: | iaor20164453 |
Volume: | 28 |
Issue: | 4 |
Start Page Number: | 736 |
End Page Number: | 751 |
Publication Date: | Nov 2016 |
Journal: | INFORMS Journal on Computing |
Authors: | Malaguti Enrico, Furini Fabio, Thomopulos Dimitri |
Keywords: | programming: integer, cutting stock, heuristics |
We propose a framework to model general guillotine restrictions in two‐dimensional cutting problems formulated as mixed‐integer linear programs (MIPs). The modeling framework requires a pseudopolynomial number of variables and constraints, which can be effectively enumerated for medium‐size instances. Our modeling of general guillotine cuts is the first one that, once it is implemented within a state‐of‐the‐art MIP solver, can tackle instances of challenging size. We mainly concentrate our analysis on the guillotine two‐dimensional knapsack problem (G2KP), for which a model, and an exact procedure able to significantly improve the computational performance, are given. We also show how the modeling of general guillotine cuts can be extended to other relevant problems such as the guillotine two‐dimensional cutting stock problem and the guillotine strip packing problem (GSPP). Finally, we conclude the paper discussing an extensive set of computational experiments on G2KP and GSPP benchmark instances from the literature.