Absolutely.
Ray
> On Feb 16, 2015, at 12:11 PM, Bouchekara Houssem
> <[email protected]> wrote:
>
> Iam not using runopf but I have implemented my one OPF using MATPOWER
> functions.
> Another question, I guess that providing the Jacobian structure, Hessian and
> Hessian structure will speed up the convergence?
>
>
> On 2/16/2015 3:21 PM, Ray Zimmerman wrote:
>> Again, it is not clear to me whether you are simply using MATPOWER’s OPF
>> (i.e. runopf) or implementing your own. It would seem you’re implementing
>> your own since the IPOPT output indicates that the Jacobian structure,
>> Hessian and Hessian structure are not supplied. With MATPOWER’s OPF
>> implementation that should not be the case. Here’s what I get …
>>
>> >> mpopt = mpoption('out.all', 0, 'verbose', 2, 'opf.ac.solver', 'IPOPT');
>> >> runopf('case30', mpopt)
>>
>> MATPOWER Version 5.1-dev, 06-Feb-2015 -- AC Optimal Power Flow
>> This is Ipopt version 3.10.3, running with linear solver mumps.
>>
>> Number of nonzeros in equality constraint Jacobian...: 454
>> Number of nonzeros in inequality constraint Jacobian.: 324
>> Number of nonzeros in Lagrangian Hessian.............: 254
>>
>> Total number of variables............................: 71
>> variables with only lower bounds: 0
>> variables with lower and upper bounds: 42
>> variables with only upper bounds: 0
>> Total number of equality constraints.................: 60
>> Total number of inequality constraints...............: 82
>> inequality constraints with only lower bounds: 0
>> inequality constraints with lower and upper bounds: 0
>> inequality constraints with only upper bounds: 82
>>
>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr
>> ls
>> 0 4.9036963e+02 1.21e+00 1.06e+01 0.0 0.00e+00 - 0.00e+00 0.00e+00
>> 0
>> 1 5.2670003e+02 4.79e-01 1.87e+02 0.1 1.28e+00 - 3.77e-01
>> 5.58e-01h 1
>> 2 5.7233174e+02 1.44e-02 8.54e+01 -0.4 6.07e-01 - 1.00e+00
>> 1.00e+00h 1
>> 3 5.7307970e+02 1.39e-02 5.98e+01 -1.0 9.22e-02 - 9.99e-01
>> 2.91e-01h 1
>> 4 5.7635279e+02 5.84e-03 1.90e+02 -1.3 1.49e-01 - 1.00e+00
>> 1.00e+00h 1
>> 5 5.7698733e+02 9.81e-04 6.93e+00 -2.0 6.20e-02 - 1.00e+00
>> 1.00e+00h 1
>> 6 5.7693657e+02 7.09e-05 5.84e+00 -2.9 1.30e-02 - 1.00e+00
>> 1.00e+00h 1
>> 7 5.7689674e+02 1.42e-05 6.89e-01 -3.8 7.65e-03 - 1.00e+00
>> 1.00e+00h 1
>> 8 5.7689223e+02 9.17e-06 5.46e-02 -5.3 6.06e-03 - 1.00e+00
>> 1.00e+00h 1
>> 9 5.7689227e+02 1.58e-06 1.08e-02 -6.8 2.65e-03 - 1.00e+00
>> 1.00e+00h 1
>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr
>> ls
>> 10 5.7689232e+02 2.06e-07 1.63e-03 -8.3 9.69e-04 - 1.00e+00
>> 1.00e+00h 1
>> 11 5.7689233e+02 1.32e-08 1.19e-04 -9.3 2.47e-04 - 1.00e+00
>> 1.00e+00h 1
>> 12 5.7689233e+02 1.13e-10 1.08e-06 -11.0 2.29e-05 - 1.00e+00
>> 1.00e+00h 1
>> 13 5.7689233e+02 1.36e-14 9.86e-11 -11.0 2.15e-07 - 1.00e+00
>> 1.00e+00h 1
>>
>> Number of Iterations....: 13
>>
>> (scaled) (unscaled)
>> Objective...............: 1.3985268672263120e+02 5.7689233273085370e+02
>> Dual infeasibility......: 9.8586584428882276e-11 4.0666966076913940e-10
>> Constraint violation....: 1.3558539391522494e-14 1.3558539391522494e-14
>> Complementarity.........: 1.0529404232602505e-11 4.3433792459485328e-11
>> Overall NLP error.......: 9.8586584428882276e-11 4.0666966076913940e-10
>>
>>
>> Number of objective function evaluations = 14
>> Number of objective gradient evaluations = 14
>> Number of equality constraint evaluations = 14
>> Number of inequality constraint evaluations = 14
>> Number of equality constraint Jacobian evaluations = 14
>> Number of inequality constraint Jacobian evaluations = 14
>> Number of Lagrangian Hessian evaluations = 13
>> Total CPU secs in IPOPT (w/o function evaluations) = 0.035
>> Total CPU secs in NLP function evaluations = 0.046
>>
>> EXIT: Optimal Solution Found.
>> >>
>>
>>
>> Regarding the issue of the objective function decreasing with each
>> iteration, that is not necessarily to be expected with primal-dual interior
>> point solvers such as the one used by IPOPT. The objective function may need
>> to increase in order to improve feasibility.
>>
>> Ray
>>
>>
>>
>>
>>> On Feb 14, 2015, at 2:33 PM, Bouchekara Houssem
>>> <[email protected] <mailto:[email protected]>> wrote:
>>>
>>> Dear all
>>> I am trying to solve the OPF using the IPOPT solver (application on the
>>> IEEE 30 bus test system).
>>> However, I have some issues.
>>>
>>> The first one is that this solver takes many iterations and at the end, I
>>> receive the message "Maximum Number of Iterations Exceeded.". if I increase
>>> the number of iterations I obtain the same message on the time of
>>> simulation !!!
>>>
>>> The second issue or question is that the objective function keep changing
>>> but not always decreasing as you can see in the herewith results. I have
>>> run the same problem using the fmincon function the objective function does
>>> not increase at all it decreases all the time until convergence !!!
>>>
>>> Regards
>>>
>>>
>>> Results
>>> %-------------------------------------------------------------------------------------------------------------------
>>> ------------------------------------------------------
>>> Nonlinear Program (NLP) Optimization
>>> min f(x)
>>> s.t. lb <= x <= ub
>>> cl <= c(x) <= cu
>>> ------------------------------------------------------
>>> Problem Properties:
>>> # Decision Variables: 24
>>> # Constraints: 233
>>> # Bounds: 48
>>> # Nonlinear Inequality: 185
>>> ------------------------------------------------------
>>> Solver Parameters:
>>> Solver: IPOPT
>>> Objective Gradient: @(x)mklJac(prob.fun,x,1) [numdiff]
>>> Constraint Jacobian: @(x)mklJac(prob.nlcon,x,nnl) [numdiff]
>>> Jacobian Structure: Not Supplied
>>> Lagrangian Hessian: Not Supplied
>>> Hessian Structure: Not Supplied
>>> ------------------------------------------------------
>>>
>>> ******************************************************************************
>>> 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
>>> <http://projects.coin-or.org/Ipopt>
>>> ******************************************************************************
>>>
>>> This is Ipopt version 3.11.7, running with linear solver ma57.
>>>
>>> Number of nonzeros in equality constraint Jacobian...: 0
>>> Number of nonzeros in inequality constraint Jacobian.: 2712
>>> Number of nonzeros in Lagrangian Hessian.............: 0
>>>
>>> Total number of variables............................: 24
>>> variables with only lower bounds: 0
>>> variables with lower and upper bounds: 24
>>> variables with only upper bounds: 0
>>> Total number of equality constraints.................: 0
>>> Total number of inequality constraints...............: 113
>>> inequality constraints with only lower bounds: 0
>>> inequality constraints with lower and upper bounds: 72
>>> inequality constraints with only upper bounds: 41
>>>
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 0 8.2505796e+002 3.92e+001 2.39e+000 0.0 0.00e+000 - 0.00e+000
>>> 0.00e+000 0
>>> 1 8.2333913e+002 3.43e+001 2.88e+001 0.0 3.26e+000 - 4.40e-001
>>> 7.91e-002f 2
>>> 2 8.1521317e+002 0.00e+000 6.48e+001 -0.4 5.64e+000 - 8.84e-001
>>> 1.00e+000f 1
>>> 3 8.0493896e+002 0.00e+000 6.52e+001 0.0 3.96e+001 - 8.87e-001
>>> 4.80e-001f 2
>>> 4 8.0277302e+002 0.00e+000 2.39e+001 -0.1 3.95e+000 - 9.88e-001
>>> 1.00e+000h 1
>>> 5 8.0079336e+002 0.00e+000 3.27e+001 -0.8 5.65e+000 - 9.86e-001
>>> 1.00e+000f 1
>>> 6 7.9975232e+002 0.00e+000 1.50e+001 -1.3 1.64e+000 - 9.99e-001
>>> 7.80e-001f 1
>>> 7 7.9977509e+002 0.00e+000 1.70e+001 -1.1 1.52e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> 8 7.9947341e+002 0.00e+000 2.73e+000 -1.7 7.49e-001 - 9.98e-001
>>> 1.00e+000h 1
>>> 9 7.9933411e+002 0.00e+000 1.06e+001 -2.2 2.68e+000 - 9.99e-001
>>> 1.00e+000h 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 10 7.9931298e+002 0.00e+000 1.50e+001 -1.9 4.96e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 11 7.9945021e+002 0.00e+000 2.00e+001 -1.6 9.10e+000 - 1.00e+000
>>> 4.53e-001f 2
>>> 12 7.9940918e+002 0.00e+000 5.80e+000 -1.7 2.61e+000 - 7.69e-001
>>> 1.00e+000h 1
>>> 13 7.9935727e+002 0.00e+000 9.48e+000 -1.7 5.58e+000 - 8.33e-001
>>> 2.62e-001h 2
>>> 14 7.9970882e+002 0.00e+000 1.04e+001 -1.7 4.50e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 15 7.9936389e+002 0.00e+000 1.04e+001 -1.7 3.89e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 16 7.9932908e+002 0.00e+000 2.52e+000 -1.7 1.06e+001 - 5.30e-001
>>> 8.14e-002h 3
>>> 17 7.9940245e+002 0.00e+000 9.01e+000 -1.7 9.80e-001 - 1.00e+000
>>> 1.00e+000h 1
>>> 18 8.0110400e+002 0.00e+000 2.25e+001 -1.7 1.04e+001 - 5.27e-001
>>> 1.00e+000H 1
>>> 19 7.9946399e+002 0.00e+000 4.25e+000 -1.7 1.20e+001 - 1.00e+000
>>> 1.00e+000F 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 20 7.9948550e+002 0.00e+000 1.00e+001 -1.3 1.24e+001 - 1.00e+000
>>> 2.28e-001f 2
>>> 21 7.9975197e+002 0.00e+000 1.65e+001 -1.5 3.80e+000 - 7.44e-001
>>> 1.00e+000h 1
>>> 22 8.0029390e+002 0.00e+000 4.95e+001 -1.5 4.78e+000 - 1.00e+000
>>> 7.66e-001H 1
>>> 23 7.9969885e+002 0.00e+000 3.75e+001 -1.5 7.79e+000 - 4.43e-001
>>> 7.55e-001F 1
>>> 24 8.0153952e+002 0.00e+000 5.42e+001 -1.5 6.09e+000 - 3.71e-001
>>> 1.00e+000H 1
>>> 25 8.0083849e+002 0.00e+000 5.53e+001 -1.5 9.48e+000 - 3.14e-001
>>> 1.60e-001f 3
>>> 26 8.0055898e+002 0.00e+000 5.68e+001 -1.5 7.24e+001 - 1.35e-001
>>> 2.09e-002f 3
>>> 27 7.9993130e+002 0.00e+000 2.14e+001 -1.5 1.56e+001 - 1.22e-001
>>> 1.16e-001f 2
>>> 28 7.9966609e+002 0.00e+000 2.34e+001 -1.5 1.13e+001 - 1.91e-001
>>> 2.55e-001h 1
>>> 29 7.9951187e+002 0.00e+000 4.68e+000 -1.5 1.61e+001 - 7.25e-002
>>> 2.62e-001f 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 30 8.0267261e+002 0.00e+000 2.31e+001 -1.5 9.14e+000 - 6.12e-001
>>> 9.49e-001H 1
>>> 31 8.0226367e+002 0.00e+000 1.04e+001 -1.5 1.01e+001 - 3.30e-001
>>> 8.99e-002f 3
>>> 32 8.0192666e+002 0.00e+000 1.32e+001 -1.5 2.47e+001 - 8.06e-002
>>> 2.93e-002f 4
>>> 33 8.0132986e+002 0.00e+000 9.01e+000 -1.5 1.40e+001 - 5.76e-001
>>> 1.32e-001f 1
>>> 34 8.0105092e+002 0.00e+000 6.84e+000 -1.5 7.34e+000 - 8.30e-001
>>> 9.60e-002f 3
>>> 35 7.9977021e+002 0.00e+000 3.28e+001 -1.5 9.26e+000 - 3.27e-001
>>> 8.37e-001F 1
>>> 36 8.0033089e+002 0.00e+000 4.86e+001 -1.5 4.62e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 37 7.9996104e+002 0.00e+000 1.06e+001 -1.5 5.43e+000 - 1.96e-001
>>> 1.75e-001f 2
>>> 38 7.9951421e+002 0.00e+000 9.42e+000 -1.5 1.59e+001 - 2.53e-001
>>> 1.96e-001f 2
>>> 39 7.9967929e+002 0.00e+000 3.01e+001 -1.5 3.16e+000 - 9.19e-001
>>> 7.79e-001H 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 40 7.9962530e+002 0.00e+000 2.19e+001 -1.5 6.91e+000 - 1.80e-001
>>> 1.78e-001h 3
>>> 41 7.9951740e+002 0.00e+000 1.26e+000 -1.5 1.88e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> 42 8.0007055e+002 0.00e+000 9.26e+000 -1.5 3.65e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 43 7.9994265e+002 0.00e+000 7.74e+000 -1.5 7.16e+000 - 5.93e-001
>>> 9.68e-002h 4
>>> 44 7.9969538e+002 0.00e+000 6.51e+000 -1.5 7.45e+000 - 6.32e-001
>>> 1.92e-001h 2
>>> 45 7.9957525e+002 0.00e+000 4.13e+000 -1.5 1.30e+001 - 4.92e-001
>>> 5.31e-002h 3
>>> 46 7.9993363e+002 0.00e+000 2.71e+001 -1.5 4.17e+000 - 4.89e-001
>>> 1.00e+000H 1
>>> 47 7.9973977e+002 0.00e+000 1.60e+001 -1.5 5.74e+000 - 6.88e-001
>>> 3.02e-001h 2
>>> 48 7.9989765e+002 0.00e+000 2.33e+001 -1.5 4.88e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 49 7.9983511e+002 0.00e+000 2.31e+001 -1.5 1.74e+001 - 6.39e-001
>>> 5.01e-002h 5
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 50 7.9970425e+002 0.00e+000 1.59e+001 -1.5 2.09e+001 - 2.33e-001
>>> 8.10e-002h 3
>>> 51 7.9955418e+002 0.00e+000 5.09e+000 -1.5 1.94e+001 - 2.51e-001
>>> 6.63e-002f 2
>>> 52 7.9950139e+002 0.00e+000 3.11e+000 -1.5 6.47e+000 - 4.13e-001
>>> 8.04e-002h 4
>>> 53 7.9944413e+002 0.00e+000 1.92e+000 -1.5 3.36e+000 - 8.24e-001
>>> 2.06e-001h 3
>>> 54 8.0126819e+002 0.00e+000 3.56e+001 -1.5 8.76e+000 - 6.44e-001
>>> 1.00e+000H 1
>>> 55 7.9945686e+002 0.00e+000 2.26e+000 -1.5 9.10e+000 - 1.00e+000
>>> 1.00e+000F 1
>>> 56 7.9950057e+002 0.00e+000 1.04e+001 -1.5 1.95e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 57 7.9942217e+002 0.00e+000 1.84e+001 -1.7 1.70e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> 58 8.0023640e+002 0.00e+000 6.79e+001 -1.8 2.88e+000 - 2.83e-001
>>> 1.00e+000H 1
>>> 59 8.0004652e+002 0.00e+000 5.87e+001 -1.8 6.11e+000 - 5.91e-001
>>> 9.88e-002h 4
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 60 7.9981714e+002 0.00e+000 5.01e+001 -1.8 2.04e+001 - 7.88e-002
>>> 4.40e-002f 4
>>> 61 7.9975653e+002 0.00e+000 4.73e+001 -1.8 9.31e+000 - 8.23e-001
>>> 2.59e-002h 4
>>> 62 7.9970454e+002 0.00e+000 4.19e+001 -1.8 3.96e+000 - 4.82e-001
>>> 3.85e-002h 5
>>> 63 7.9962939e+002 0.00e+000 3.88e+001 -1.8 4.97e+000 - 2.21e-001
>>> 5.05e-002h 5
>>> 64 7.9953788e+002 0.00e+000 3.19e+001 -1.8 1.07e+001 - 3.03e-001
>>> 1.32e-001h 2
>>> 65 7.9939133e+002 0.00e+000 1.33e+001 -1.8 1.27e+001 - 2.71e-001
>>> 1.24e-001h 2
>>> 66 7.9939690e+002 0.00e+000 4.01e+000 -1.8 7.99e+000 - 3.71e-001
>>> 4.06e-001h 2
>>> 67 7.9936697e+002 0.00e+000 4.73e+000 -1.8 4.44e+001 - 3.91e-001
>>> 3.41e-002h 4
>>> 68 7.9936784e+002 0.00e+000 1.89e+000 -1.8 1.39e+001 - 9.19e-001
>>> 1.23e-001h 4
>>> 69 7.9943394e+002 0.00e+000 1.13e+001 -1.8 7.41e+000 - 3.90e-001
>>> 3.38e-001w 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 70 8.0333982e+002 3.88e-001 6.64e+001 -1.8 1.21e+001 - 4.03e-001
>>> 9.33e-001w 1
>>> 71 8.0004084e+002 2.01e+000 2.23e+001 -1.8 9.50e+000 - 1.75e-001
>>> 8.22e-001w 1
>>> 72 7.9932137e+002 0.00e+000 4.72e+000 -1.8 8.14e+001 - 3.90e-001
>>> 1.69e-001h 1
>>> 73 7.9933546e+002 0.00e+000 1.20e+001 -1.8 2.20e+000 - 1.00e+000
>>> 4.15e-001h 2
>>> 74 7.9930951e+002 0.00e+000 8.03e+000 -1.8 2.31e+001 - 2.28e-001
>>> 5.44e-002h 4
>>> 75 8.0016365e+002 0.00e+000 6.14e+001 -1.9 2.00e+000 - 9.59e-001
>>> 1.00e+000H 1
>>> 76 7.9955770e+002 0.00e+000 4.24e+001 -2.0 5.35e+000 - 7.40e-001
>>> 4.29e-001f 1
>>> 77 7.9939342e+002 0.00e+000 1.45e+001 -2.0 2.40e+001 - 1.52e-001
>>> 9.57e-002h 2
>>> 78 7.9925263e+002 0.00e+000 1.21e+001 -2.0 1.69e+001 - 1.18e-001
>>> 1.51e-001h 2
>>> 79 7.9941302e+002 0.00e+000 1.24e+001 -1.3 1.89e+001 - 9.77e-001
>>> 1.77e-001h 2
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 80 8.0134560e+002 0.00e+000 3.00e+001 -1.4 4.81e+000 - 6.41e-001
>>> 1.00e+000h 1
>>> 81 7.9998500e+002 0.00e+000 1.73e+001 -1.4 7.31e+000 - 9.05e-001
>>> 8.39e-001f 1
>>> 82 7.9953189e+002 0.00e+000 4.34e+000 -1.4 2.20e+001 - 7.03e-001
>>> 1.77e-001f 2
>>> 83 7.9959732e+002 0.00e+000 1.07e+001 -1.4 3.78e+000 - 6.33e-001
>>> 1.00e+000h 1
>>> 84 8.0004713e+002 0.00e+000 3.44e+001 -1.4 4.05e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 85 7.9988950e+002 0.00e+000 3.31e+001 -1.4 3.13e+001 - 5.62e-001
>>> 9.57e-002f 2
>>> 86 7.9955465e+002 0.00e+000 1.76e+001 -1.4 1.50e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> 87 7.9949662e+002 0.00e+000 7.54e+000 -1.4 3.70e+000 - 2.85e-001
>>> 1.85e-001h 3
>>> 88 7.9959288e+002 0.00e+000 1.71e+001 -1.4 1.39e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> 89 8.0006272e+002 0.00e+000 1.37e+001 -1.4 5.26e+000 - 1.00e+000
>>> 1.00e+000h 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 90 7.9980392e+002 0.00e+000 1.44e+001 -1.4 6.97e+000 - 4.93e-001
>>> 2.01e-001h 2
>>> 91 7.9963251e+002 0.00e+000 8.20e+000 -1.4 9.82e+000 - 5.22e-001
>>> 1.65e-001h 3
>>> 92 7.9959672e+002 0.00e+000 2.45e+000 -1.4 3.24e+001 - 7.30e-001
>>> 1.55e-001h 2
>>> 93 7.9951429e+002 0.00e+000 3.42e+000 -1.4 3.75e+000 - 8.01e-001
>>> 1.00e+000h 1
>>> 94 7.9972009e+002 0.00e+000 1.76e+001 -1.4 2.53e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> 95 7.9971154e+002 0.00e+000 2.36e+001 -1.4 2.37e+000 - 7.73e-001
>>> 1.00e+000H 1
>>> 96 7.9958228e+002 0.00e+000 1.80e+001 -1.4 1.65e+001 - 4.70e-001
>>> 1.12e-001h 2
>>> 97 7.9950114e+002 0.00e+000 7.95e+000 -1.4 3.83e+000 - 1.00e+000
>>> 2.99e-001h 2
>>> 98 7.9964810e+002 0.00e+000 1.43e+001 -1.4 2.33e+000 - 9.82e-001
>>> 1.00e+000H 1
>>> 99 7.9958083e+002 0.00e+000 9.04e+000 -1.4 2.42e+000 - 1.00e+000
>>> 1.00e+000H 1
>>> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du
>>> alpha_pr ls
>>> 100 7.9957133e+002 0.00e+000 5.14e+000 -1.4 1.19e+001 - 4.74e-001
>>> 1.06e-001h 3
>>>
>>> Number of Iterations....: 100
>>>
>>> (scaled) (unscaled)
>>> Objective...............: 7.9957132849034247e+002 7.9957132849034247e+002
>>> Dual infeasibility......: 5.1351489054861581e+000 5.1351489054861581e+000
>>> Constraint violation....: 0.0000000000000000e+000 0.0000000000000000e+000
>>> Complementarity.........: 6.3178225777153776e-002 6.3178225777153776e-002
>>> Overall NLP error.......: 5.1351489054861581e+000 5.1351489054861581e+000
>>>
>>>
>>> Number of objective function evaluations = 331
>>> Number of objective gradient evaluations = 101
>>> Number of equality constraint evaluations = 0
>>> Number of inequality constraint evaluations = 331
>>> Number of equality constraint Jacobian evaluations = 0
>>> Number of inequality constraint Jacobian evaluations = 101
>>> Number of Lagrangian Hessian evaluations = 0
>>> Total CPU secs in IPOPT (w/o function evaluations) = 2.533
>>> Total CPU secs in NLP function evaluations = 125.944
>>>
>>> EXIT: Maximum Number of Iterations Exceeded.
>>> %-------------------------------------------------------------------------------------------------------------------
>>
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