The Rosenbrock function, f(x,y)=(1-x)^2 + 100(y-x^2)^2, is a classic test function in optimisation theory. It is sometimes referred to as Rosenbrock's banana function due to the shape of its contour lines. The global minimum is at the point (1,1) that lies inside a long, narrow valley; some numerical solvers can take a long time to converge to it. In this Demonstration you can compare the performance of six different numerical methods (Conjugate Gradient, Levenberg-Marquardt, Newton, Quasi-Newton, Principal Axis and Interior Point) when they are applied to the Rosenbrock functionComponente Curricular::Educação Superior::Ciências Exatas e da Terra::Matemática