[Ipopt] help diagnosing Ipopt error

[Jorge Fernández de Cossío Díaz]

How can I increase the print level of Ipopt, from Julia/JuMP?

On Fri, May 13, 2016 at 8:39 AM, Stefan Vigerske <stefan at math.hu-berlin.de>
wrote:

> Hi,
>
> I think the starting point cannot be evaluated, maybe T[i] + z[i] is 0 for
> some i, or some division in 0 in the last constraint?
>
> Increasing the print level of Ipopt may also help.
>
> Stefan
>
>
> On 05/13/2016 02:12 PM, Jorge Fernández de Cossío Díaz wrote:
>
>> I am using JuMP + Ipopt to solve a nonlinear constrained optimization
>> problem. The problem is of this form:
>>
>> P = JuMP.Model()
>> JuMP. at variable(P, x0[j] ≤ x[j=1:N] ≤ x1[j])
>> JuMP. at variable(P, y0[j] ≤ y[j=1:M] ≤ y1[j])
>> JuMP. at variable(P, z0[j] ≤ z[j=1:M] ≤ z1[j])
>> JuMP. at variable(P, lambda ≥ 0)
>> JuMP. at variable(P, Q ≥ 0)
>> JuMP. at constraint(P, matrix * x .== lambda * b - y)
>> for i = 1:M
>>     JuMP. at NLconstraint(P, y[i] ≤ z[i] / (T[i] + z[i]))
>>     JuMP. at NLconstraint(P, z[i] == R[i] - y[i] * Q)
>> end
>> JuMP. at NLconstraint(P, lambda / prod{1. + z[i] / R2[i], i=1:M} -
>> prod{z[i] /
>> (R3[i] + z[i]), i=1:M} - C ≥ 0)
>>
>> where x0, x1, y0, ..., z1 are vectors previously defined, 'matrix' is a
>> MxN
>> matrix, also previously defined, 'b' an M-vector, T, R, R2, R3 also
>> previously defined vectors.
>>
>> I copied below the full Ipopt output containing the error I get when I try
>> to optimize this model. I have no clue of where to start looking for the
>> source of this error. Can someone point out common causes of this error,
>> so
>> I can get started?
>>
>>
>>
>> ******************************************************************************
>> This program contains Ipopt, a library for large-scale nonlinear
>> optimization.
>>  Ipopt is released as open source code under the Eclipse Public License
>> (EPL).
>>          For more information visit http://projects.coin-or.org/Ipopt
>>
>> ******************************************************************************
>>
>> This is Ipopt version 3.12.1, running with linear solver mumps.
>> NOTE: Other linear solvers might be more efficient (see Ipopt
>> documentation).
>>
>> Number of nonzeros in equality constraint Jacobian...:     1495
>> Number of nonzeros in inequality constraint Jacobian.:      501
>> Number of nonzeros in Lagrangian Hessian.............:    27107
>>
>> Total number of variables............................:      505
>>                      variables with only lower bounds:      256
>>                 variables with lower and upper bounds:      231
>>                      variables with only upper bounds:        1
>> Total number of equality constraints.................:      458
>> Total number of inequality constraints...............:      230
>>         inequality constraints with only lower bounds:        1
>>    inequality constraints with lower and upper bounds:        0
>>         inequality constraints with only upper bounds:      229
>>
>>
>> Number of Iterations....: 0
>>
>> Number of objective function evaluations             = 0
>> Number of objective gradient evaluations             = 1
>> Number of equality constraint evaluations            = 1
>> Number of inequality constraint evaluations          = 1
>> Number of equality constraint Jacobian evaluations   = 1
>> Number of inequality constraint Jacobian evaluations = 1
>> Number of Lagrangian Hessian evaluations             = 0
>> Total CPU secs in IPOPT (w/o function evaluations)   =      0.060
>> Total CPU secs in NLP function evaluations           =      0.004
>>
>> EXIT: Invalid number in NLP function or derivative detected.
>> WARNING: Ipopt finished with status Invalid_Number_Detected
>> WARNING: Not solved to optimality, status: Error
>>
>>
>>
>> _______________________________________________
>> Ipopt mailing list
>> Ipopt at list.coin-or.org
>> http://list.coin-or.org/mailman/listinfo/ipopt
>>
>>
>
> --
> http://www.gams.com/~stefan
>
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