Benchmarking Nonlinear Constrained Optimization algorithms

This is work in progress

There are two types of problems: fixed problems and scalable ones. A concrete problem inherites from the base classe base.ConstrainedTestProblem.

A fixed problem has fixed dimension dim and number of inequality constraints m. Most of its methods are static hence it can be used without instantiation. However the property m cannot be accessed in this class. Later improvement is to define class properties.

A scalable problem needs instantiation with dimension and number of constraints.

• Add the decorators arrayize and realfunction everywhere.
• Implement the gradient everywhere it is possible

Just do pip install . in this repository, everything relies on numpy and scipy.optimize if you want to run experiments.