Dorian Henricot

Hello, I want to optimize a function f(x,k_n) with x optimization variable and k(n) parameter. We iterate N times over k_n. The way that works is for each k(n) to use adigatorGenFiles4Ipopt and feed the output functions to ipopt. However, this requires to recalculate N times the gradient, jacobian, etc. I would like to know whether it is possible to generate upfront the gradient(x,k0), jacobian(x,k0), etc, and then for each iteration define funcs.gradient=funcs.gradient(x,k_n), etc, and feed funcs...