Leftover Problem Dataset Generator

This dataset generator from the leftover problem is based in the work:

Bressan, G.M., da Silva, E.B., Pimenta-Zanon, M.H., da Silva Lizzi, E.A. (2022). Classification of Leftovers from the Stock Cutting Process. In: Pereira, A.I., Košir, A., Fernandes, F.P., Pacheco, M.F., Teixeira, J.P., Lopes, R.P. (eds) Optimization, Learning Algorithms and Applications. OL2A 2022. Communications in Computer and Information Science, vol 1754. Springer, Cham. https://doi.org/10.1007/978-3-031-23236-7_23

This project is licensed under the Apache-2.0 License

Dependencies

This project is build with the Python 3.10.2

You need to have installed the NumPy package. if you already have Python, you can install NumPy with:

conda install numpy or pip install numpy

Usage

Installation

If you already have Git, you can download this script with:

git clone https://github.com/ximiraxelo/leftoverproblem

Generating a dataset

To generate a dataset call the function generate_dataset()

objs, itens, demands = generate_dataset(n_itens, n_obj, l_types, L_types, d_types, l_min, l_max, L_min, L_max, d_min, d_max)

Inputs:

• n_itens (int): the number of the itens per object
• n_obj (int): the number of objects
• l_types (int): the amount of types of sizes of the itens
• L_tpyes (int): the amount of types of sizes of the objects
• d_types (int): the amount of types of the itens demands
• l_min (int) and l_max (int): the minimum and maximum size of the itens
• L_min (int) and L_min (int): the minimum and maximum size of the objects
• d_min (int) and d_max (int): the minimum and maximum of the itens demands

Outputs:

• objs (list): a list with n_objs length that contains the objects sizes
• itens (list): a list with the shape (n_obs, n_itens) that contains the itens sizes
• demands (list): a list with the shape (n_obs, n_itens) that contains the itens demands

---

You can use the parameters according to "The constrained compartmentalised knapsack problem, F. P. Marques and M. N. Arenales, 2007"

In this case you only need to specify n_itens, n_obj, l_types, L_types, d_types. See the example:

objs, itens, demands = generate_dataset(n_itens=20, n_obj=10, l_types=5, L_types=3, d_types=2)

---

Saving the dataset

The generated dataset can be saved in .npy files.

See more about .npy files in the NumPy documentation

To save a generated dataset call the function save_dataset()

save_dataset(objs, itens, demands, DATASET_PATH)

Inputs:

• objs (list), itens (list), demands (list): the generated data from the generate_dataset() function
• DATASET_PATH (str): the absolute path to save the .npy files

Citation

If you use this script in your work, please cite us