I am using JuMP.jl to develop NLOptControl.jl to solve optimal control problems and I have dealt with an IPOPT issue for some time now, where the dual infeasibility of my constraints are very high and eventually the problems converge to a local point of infeasibility. But, when I extract this “infeasible solution” it looks perfectly fine (it does not violate any of the constraints). A few months back, I would adjust the convergence criteria so that it works, but the values that I had previously found worked no longer work. And since I am developing this tool, I don’t want the user to have to worry too much about tuning these things. Any thoughts?
A similar question was raised some time ago about this issue here
but, the problem that they hypothesized it was would not be an issue for me because I am using the hessian and not the BFGS approximation of the hessian.