fsam_paper is a GitHub repository containing all the tables and simulations results
shown in the paper:
All the simulation studies carried out in this work use the routines implemented in fsam, which requires a GUROBI license to solve the optimization problems.
The current version of the project is structured as follows:
- fsam_paper: the main directory of the project, which
consist of:
- R_scripts: contains the code to the other state-of-the-art algorithms used to compare our approach.
- fsam_comparison.py: the code used in the comparison of FSAM with the other state-of-the-art methodologies (Section 5.1.2).
- fsam_ws_performance.py: the code used in the comparison of the MIQP formulation and FSAM used as warm start (Section 5.1.1).
- matheuristic_performance.py: the code used in the comparison of the MIQP formulation and FSAM (Section 5.1.1).
- matheuristic_performance.py: the sensibility analysis performed on the destroy size and the patience parameters (Supplementary Material).
- small_datasets.py: the code used in the real-world data sets (Section 5.2.1).
- superconductors.py: the code used in the real data set application of superconductivity data (Section 5.2.2).
- tables.ipynb: A Jupyter notebook containing the code used to generate the tables and the figures of the paper.
- utils.py: Auxiliary code for the rest of the scripts.
- data: a folder containing CSV and parquet files with simulated and real data sets results.
fsam_paper mainly depends on the following packages:
If you have encountered any problem or doubt while using fsam, please feel free to let
me know by sending me an email:
- Name: Manuel Navarro García (he/his)
- Email: manuelnavarrogithub@gmail.com
If you find fsam or fsam_paper useful, please cite it in your publications.