hadrian_min is a stochastic, hill climbing minimization algorithm. It uses a stratified sampling technique (Latin Hypercube) to get good coverage of potential new points. It also uses vectorized function evaluations to drive concurrent function evaluations.
It is named after the Roman Emperor Hadrian, the most famous Latin hill mountain climber of ancient times.
It is implemented in 2D only, but could be exteneded to higher/lower dimensions if you workout the how to do the sampling in a more general way or for your special case.