This is a reimplementation of benchmarkfcns for use with CasADi. The Python module is intended to be used to generate the required functions as either MX or SX CasADi functions. Example usage:

import casadi as cs
import benchmarkfcns2casadi as bm

rosenbrock_func, input_domains, minima = bm.generate_rosenbrock(n=2, a=1, b=100, data_type=cs.SX)
print(rosenbrock_func)

• Specifying local and global minima
• Currently only has unconstrained optimization problems, add generic constrained problems?