[Ipopt] run time constraint violation

[Ming Ji]

On Wed, Apr 4, 2012 at 1:53 AM, Hans Pirnay <hans.pirnay at rwth-aachen.de>wrote:

> Ipopt does not guarantee the equality constraints to hold at all
> times. However, the bounds you specified on the variables will always
> hold. Therefore, if you have a term like
>
> h(x) = sqrt(f(x))
>
> try introducing a variable y with
>
> y = f(x)
> h(x) = sqrt(y)
> y>=0
>
> or better yet, get rid of the sqrt altogether
>
> y = f(x)
> z*z = y
> h(x) = z
> y >=0
> z>=0
>
> However, note that any formulation involving bilinear terms ( x * y )
> must not be evaluated at (x=0, y=0), because of the derivatives. So
> you will need to specify starting values for y and z > epsilon
>
> hope this helps
>
> On Wed, Apr 4, 2012 at 5:34 AM, Ming Ji <finalguy at gmail.com> wrote:
> > --> Starting line search in iteration 2 <--
> > Mu has changed in line search - resetting watchdog counters.
> > Acceptable Check:
> >   overall_error =  3.3081951656527707e+01   acceptable_tol_             =
> >  9.9999999999999995e-07
> >   dual_inf      =  1.0184827638240758e+03   acceptable_dual_inf_tol_    =
> >  1.0000000000000000e+10
> >   constr_viol   =  0.0000000000000000e+00   acceptable_constr_viol_tol_ =
> >  1.0000000000000000e-08
> >   compl_inf     =  4.5618525445151024e+00   acceptable_compl_inf_tol_   =
> >  1.0000000000000000e-02
> >   curr_obj_val_ =  2.7727963512437492e-01   last_obj_val                =
> >  1.3239460189118296e-01
> >   fabs(curr_obj_val_-last_obj_val_)/Max(1., fabs(curr_obj_val_)) =
> >  1.4488503323319196e-01 acceptable_obj_change_tol_ =
>  1.0000000000000000e+20
> > test iter = 2
> > The current filter has 0 entries.
> > Relative step size for delta_x = 1.790897e-01
> > minimal step size ALPHA_MIN = 6.253269E-14
> > Starting checks for alpha (primal) = 1.00e+00
> >
> >
> > On Tue, Apr 3, 2012 at 9:02 PM, Ming Ji <finalguy at gmail.com> wrote:
> >>
> >> I am trying to solve a NLP problem with IPOPT. I noticed that
> constraints
> >> can be violated during the optimization. I need to take sqrt to
> estimate one
> >> term in my target function. So it is natural to add a constraint to make
> >> sure the sqrt calculation is always valid. However, during the
> iterations,
> >> IPOPT use some trial parameters that violate this constraint. The
> >> optimization almost always terminates before it finds any solution. Any
> work
> >> around for this?
> >
> >
> >
> > _______________________________________________
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> > Ipopt at list.coin-or.org
> > http://list.coin-or.org/mailman/listinfo/ipopt
> >
>
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