[Coin-ipopt] pb with discontinuity of Hessian

[Sylvain Miossec]

Hi,

I have an optimization problem with continuous criteria and constraints 
gradients, continuous criteria hessian but discontinuous constraints 
hessians. I saw in an IPOPT paper that the conditions of use of IPOPT 
are that criteria and constraints are twice differentiable.
I would like to have an idea of the implications of the absence of twice 
differentiability for my problem. From a theoretical point of view is 
this twice differentiability is absolutely necessary to the convergence 
proof, or just for the quadratic convergence proof ? Then in a practical 
implementation, can IPOPT converge slowly ? Would it be better to smooth 
the constraints so that they are twice differentiable (which seems to be 
not that easy) ?

Any information about this would help me a lot.

Sylvain