Software

• 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.