[Ipopt] Infeasible Problem Detected when the problem is actually feasible

Filip Jorissen filip.jorissen at kuleuven.be
Fri Apr 6 03:13:02 EDT 2018


It sounds like IPOPT converges to a local point of infeasibility? I.e. your equations are non-convex and you need a good/feasible initial guess to be able to converge to a feasible (local) optimum.


Op 5 apr. 2018, om 17:27 heeft Maxime Boulay <mboulay at flogen.com<mailto:mboulay at flogen.com>> het volgende geschreven:


I am using IpOpt to solve a problem with about 20 variables and 20 constraints. I know the solution to this problem, and I have verified that my constraints are respected at the solution, there is also no error in the Derivative Checker. However, IpOpt still ends up giving me the Infeasible Problem Detected message when I run it. If I keep running it again with the "warm_start_init_point", it eventually does find the solution. This happens for many different entry values to this problem. Can anyone help me find a clue as to why this would happen?

Thank you.


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