DFO-TR:
Open-source MATLAB code for nonlinear unconstrained optimization problems based on a trust-region interpolation-based method that does not use any derivatives of the objective function. Code managed by me and co-authored by Katya Scheinberg (Cornell University), Luis Nunes Vicente (Lehigh University), Liyuan Cao (Peking University), and Oumaima Sohab (Lehigh University).
The code is available for download at https://coral.ise.lehigh.edu/lnv/dfo-tr/.
DFNDFL:
Open-source Python code for solving mixed-integer nonsmooth constrained black-box optimization problems. Co-authored by Giampaolo Liuzzi (Sapienza University of Rome), Stefano Lucidi (Sapienza University of Rome), and Francesco Rinaldi (University of Padua).
The code is available for download at http://www.iasi.cnr.it/~liuzzi/DFL/index.php/home.
BSG-N-FD, BSG-1:
Open-source Python code for solving nonlinear bilevel stochastic optimization problems. Co-authored by Griffin D. Kent and Luis Nunes Vicente.
The code is available at https://github.com/GdKent/BSG_Methods_Con_Unc.
BSG-OPT, BSG-RN, BSG-RA:
Open-source Python code for solving nonlinear bilevel multi-objective optimization problems. Co-authored by Griffin D. Kent and Luis Nunes Vicente.
The code is available at https://github.com/GdKent/BMOLL_OPT_RN_RA.
BasesNNApproxForOpt:
Open-source Python code to use neural networks as surrogate models for approximating and minimizing objective functions in optimization problems. Co-authored by Oumaima Sohab and Luis Nunes Vicente.
The code is available at https://github.com/sohaboumaima/BasesNNApproxForOpt.
randomness-team-ball-sports:
Open-source Python code to analyze randomness factors in team ball sports. Co-authored by Thaksheel N. Alleck. This code can be used with the match score dataset available at https://data.mendeley.com/datasets/2pt4vmyf27/2.
The code is available at https://github.com/thaksheel/randomness-team-ball-sports.
snee:
Open-source Python code to compute most-changing Pareto sub-fronts and knee solutions through the sensitivity knee (snee) approach.
The code is available at https://github.com/tommaso-giovannelli/snee.
TSG-N-FD, TSG-AD:
Open-source Python code for solving trilevel optimization problems. Co-authored by Griffin D. Kent and Luis Nunes Vicente.
The code is available at https://github.com/GdKent/TSG.