By means of reductions to vector packing, VPSolver can be used to solve several problems such as:
- Bin packing;
- Cutting stock;
- Cardinality constrained bin packing;
- Cutting stock with cutting knife limitation;
- Bin packing with conflicts;
- Cutting stock with binary patterns;
- Cutting stock with binary patterns and forbidden pairs.
- [Computational results on several benchmark test data sets]
By means of reductions to multiple-choice vector packing, VPSolver can be used to solve several problems such as:
- Variants of the problems from the list above that consider multiple bin types;
- Variable-sized bin packing (as an one-dimensional multiple-choice vector bin packing problem).
VPSolver includes a python interface that allows modeling other problems easily. Using the python interface, VPSolver can be used to solve problems such as:
- Many variants that happen in the industry that include cutting and packing problems as subproblems of a larger production planning problem;
- Multi-stage variants (e.g, two- and three-stage two-dimensional cutting stock problems);
- Multi-period variants (e.g., plan the production for several days with the possibility of delaying or anticipating the production of some items).
Note: Suggestions of other cutting & packing problems (including industrial applications) are welcome! [Contact]