[Ipopt] run time constraint violation
Hans Pirnay
hans.pirnay at rwth-aachen.de
Wed Apr 4 02:53:59 EDT 2012
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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