data4co 0.0.1a10

data4co provides convenient dataset generators for the combinatorial optimization problem

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()