Restoration fails when using objectivePriors about sbml2julia

[sshin23]

Ipopt sometimes face this type of convergence issue when the problem is highly nonlinaer. But in this case it seems that the solver sometimes finds the solution, depending on the random realization of the initial point. For example, in my computer, Ipopt converges if I set:

import Random; Random.seed!(3)

For this problem, I think some more problem-specific knowledge may be used to get a tighter parameter bounds, or use multiple starting point strategy.

[paulflang]

OK. This explains why I saw inconsistent behaviour. I mean inconsistent behaviour should not be unexpected given the randomisation of starting points. It is just that in my experience the choice of starting points did not have any effect in other examples. For me it is Random.seed!(4) that works. But in the end I just narrowed some of the parameter boundaries. Thanks a lot!