Data4CO
A data generator tool for Combinatorial Optimization (CO) problems, enabling customizable, diverse, and scalable datasets for benchmarking optimization algorithms.
Current support
solver
| Problem | Base | Impl. | First | Impl. | Second | Impl. | Third | Impl. | Fourth | Impl. |
|---|---|---|---|---|---|---|---|---|---|---|
| TSP | TSPSolver | ✔ | LKH | ✔ | Concorde | ✔ | NAR | 📆 | AR | 📆 |
| MIS | MISSolver | ✔ | KaMIS | ✔ | Gurobi | ✔ | -- | -- | -- | -- |
generator
| Problem | Type1 | Impl. | Type2 | Impl. | Type3 | Impl. | Type4 | Impl. |
|---|---|---|---|---|---|---|---|---|
| TSP | uniform | ✔ | gaussian | ✔ | cluster | 📆 | -- | -- |
| MIS | ER | ✔ | BA | ✔ | HK | ✔ | WS | ✔ |
✔: Supported; 📆: Planned for future versions (contributions welcomed!).
How to Install
Github
Clone with the url https://github.com/heatingma/Data4CO.git , and the following packages are required, and shall be automatically installed by pip:
Python >= 3.8
numpy>=1.24.4
networkx==2.8.8
lkh>=1.1.1
tsplib95==0.7.1
tqdm>=4.66.1
pulp>=2.8.0,
pandas>=2.0.0,
scipy>=1.10.1
PyPI It is very convenient to directly use the following commands
pip install data4co
How to Use Solver (TSPLKHSolver as example)
from data4co.solver import TSPLKHSolver
tsp_lkh_solver = TSPLKHSolver(lkh_max_trials=500)
tsp_lkh_solver.from_txt("path/to/read/file.txt")
tsp_lkh_solver.solve()
tsp_lkh_solver.evaluate()
tsp_lkh_solver.to_txt("path/to/write/file.txt")How to Use Generator (TSPDataGenerator as example)
from data4co import TSPDataGenerator
tsp_data_lkh = TSPDataGenerator(
num_threads=8,
nodes_num=50,
data_type="uniform",
solver="lkh",
train_samples_num=16,
val_samples_num=16,
test_samples_num=16,
save_path="path/to/save/"
)
tsp_data_lkh.generate()
