[Ipopt] empty ipopt.out + objective's decrease

[Denis Davydov]

Dear All,

Could you please advise,
I modified original C++ example (hs071_cpp) according to my problem and
experience some difficulties:

1) output of Ipopt is empty. I see it in terminal, but that's it. Running
with ./hs071_cpp > myOtput.txt   writes only some of my output with
"std::cout", but not general Ipopt output. Same with "nohup". Original C
example is ok and writes output. I have not modified any options regarding
output while coding.

Version of Ipopt: 3.7.0, solver - ma57; compilers: gcc, f++, fgortran --
version 4.3.2 (Debian 4.3.2-1.1), 64bit.

Configuration output is enclosed for any case.


2) objective function does not decrease constantly and even increases
constantly sometimes. I mean, I known the solution of this test problem:
objective = -sqrt(3.0), therefore it's strange a bit for me that the
solution goes in a wrong direction in some sense. Of course this is
constraint optimization, I don't know all the values of variables, current
point can violate constraints etc. I'm not very much into method, but this
is somehow strange for me. Could it be a result of my bad-coding?

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du
alpha_pr  ls
   0  1.0000000e+00 5.64e-13 1.00e+00   0.0 0.00e+00    -  0.00e+00
0.00e+00   0
   1  9.9993651e-01 3.07e-09 1.01e-02  -6.2 6.35e-05  -4.0 9.90e-01
1.00e+00f  1
   2  8.1572706e-01 1.13e-02 1.09e-04  -2.9 1.84e-01  -3.6 9.92e-01
1.00e+00f  1
   3  4.0527557e-01 5.62e-02 7.35e-05  -4.7 4.10e-01  -4.1 9.99e-01
1.00e+00h  1
   4 -4.5422878e-03 5.60e-02 1.15e-04  -9.2 4.10e-01  -3.6 1.00e+00
1.00e+00h  1
   5 -7.4555060e-03 2.83e-06 2.27e-03 -11.0 5.60e-02  -1.4 1.00e+00
1.00e+00h  1
   6 -7.9025588e-03 6.66e-08 1.87e-04 -11.0 4.47e-04    -  1.00e+00
1.00e+00h  1
   7 -2.1786486e-02 6.43e-05 2.29e-04 -11.0 1.39e-02  -1.9 1.00e+00
1.00e+00f  1
   8 -1.1153940e+00 3.99e-01 2.70e-04 -11.0 4.37e+00    -  1.00e+00
2.50e-01f  3
   9 -9.6325697e-01 7.72e-03 1.28e-03 -11.0 2.86e-01  -2.3 1.00e+00
1.00e+00h  1
iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du
alpha_pr  ls
  10 -1.1657772e+00 1.37e-02 4.71e-04 -11.0 2.03e-01    -  1.00e+00
1.00e+00h  1
  11 -9.5656068e-01 9.10e-04 3.42e-04 -11.0 2.03e-01  -2.8 1.00e+00
1.00e+00H  1
  12 -8.7525035e-01 5.49e-05 3.25e-04 -11.0 8.03e-02  -2.4 1.00e+00
1.00e+00H  1
  13 -7.0099697e-01 3.27e-05 2.32e-04 -11.0 1.69e-01  -2.9 1.00e+00
1.00e+00H  1
  14 -6.7595156e-01 1.39e-06 8.89e-05 -11.0 2.50e-02  -2.4 1.00e+00
1.00e+00H  1
  15 -6.7277849e-01 2.79e-09 3.76e-06 -11.0 3.17e-03  -2.9 1.00e+00
1.00e+00H  1



p/p/s/ problem I solve is quite large:

Number of nonzeros in equality constraint Jacobian...:   577081
Number of nonzeros in inequality constraint Jacobian.:   144000
Number of nonzeros in Lagrangian Hessian.............:   504000

Total number of variables............................:   144001
                     variables with only lower bounds:        0
                variables with lower and upper bounds:        0
                     variables with only upper bounds:        0
Total number of equality constraints.................:   131286
Total number of inequality constraints...............:    24000
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0

so where is no way to run Derivative checker or approximation. There is
also no way to decrease number of variables.



Thank you in advance,
Best regards,
Denis.


-- 
Denis Davydov
Department of Mechanics
Faculty of Civil Engineering
Czech Technical University
Thakurova 7, 166 29 Prague 6, Czech Republic
phone: +420-728478669
email: denis.davydov at fsv.cvut.cz


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