* Nonsmooth Optimization Solver* (NonOpt) is a software package for minimizing nonsmooth functions. It is designed to locate a minimizer (or at least a stationary point) of

$$\min_{x\in\mathbb{R}^n}\ \ f(x)$$

where \(f : \mathbb{R}^n \to \mathbb{R}\) is locally Lipschitz and continuously differentiable over a full-measure subset of \(\mathbb{R}^n\). The function \(f\) is allowed to be nonconvex.

NonOpt is written in C++. A beta version is available upon request.

**We are looking for test problems!** If you have nonsmooth (nonconvex) test problems, please let us know. We would be very interested in testing (and tuning) NonOpt with them.

## Developer

## Citing NonOpt

NonOpt is based on the algorithms described in the following papers.

- [Download PDF] F. E. Curtis and X. Que. A Quasi-Newton Algorithm for Nonconvex, Nonsmooth Optimization with Global Convergence Guarantees.
*Mathematical Programming Computation*, 7(4):399–428, 2015. [Bibtex]`@article{CurtQue15, author = {Curtis, F. E. and Que, X.}, title = {{A Quasi-Newton Algorithm for Nonconvex, Nonsmooth Optimization with Global Convergence Guarantees}}, journal = {{Mathematical Programming Computation}}, volume = {7}, number = {4}, pages = {399--428}, year = {2015}, url = {http://coral.ise.lehigh.edu/frankecurtis/files/papers/CurtQue15.pdf} }`

- [Download PDF] F. E. Curtis and X. Que. An Adaptive Gradient Sampling Algorithm for Nonsmooth Optimization.
*Optimization Methods and Software*, 28(6):1302–1324, 2013. [Bibtex]`@article{CurtQue13, author = {Curtis, F. E. and Que, X.}, title = {{An Adaptive Gradient Sampling Algorithm for Nonsmooth Optimization}}, journal = {{Optimization Methods and Software}}, volume = {28}, number = {6}, pages = {1302--1324}, year = {2013}, url = {http://coral.ise.lehigh.edu/frankecurtis/files/papers/CurtQue13.pdf} }`