[Ipopt] IPOPT options for reducing constraint violation after fewer iterations
Stefan Vigerske
stefan at math.hu-berlin.de
Thu May 11 11:01:01 EDT 2017
Hi,
if you set parameter start_with_resto, then Ipopt should first minimize
infeasibility until it finds a point which infeasibility is considerably
smaller than the starting point (I guess). When this is achieved, it
should switch back to the original problem where the original objective
function is considered again. What is meant by "considerably smaller" is
controlled by the parameter "required_infeasible_reduction"
https://www.coin-or.org/Ipopt/documentation/node50.html#SECTION0001110040000000000000
Best,
Stefan
On 05/10/2017 05:51 PM, Austin Herrema wrote:
> Hello all,
>
> I am using IPOPT implemented through OpenMDAO and am having some trouble
> understanding and controlling the stopping criteria.
>
> Here is what I'm experiencing specifically: Initially, IPOPT is able to
> find a solution that appears to be much better, although constraints are
> violated slightly (intuition tells me that adjusting a few parameters would
> likely bring it into the feasible region). From this stackoverflow
> discussion
> <http://stackoverflow.com/questions/36907064/why-does-ipopt-evaluate-objective-function-despite-breaching-constraints>
> I
> understand that "linear or nonlinear equality or inequality constraint will
> not necessarily be satisfied until the solver has finished converging at
> the final iteration," so I would like to know if I can change tolerances
> such that the solver will begin to completely satisfy constraints sooner.
> Currently, nearly all evaluations are in the infeasible regime.
>
> I realize that this approach would result in a less optimal solution, but
> my function evaluations are quite computationally expensive so I'd like to
> be able to have some kind of control over exiting earlier but with feasible
> results. It is not clear to me when looking at IPOPT termination
> documentation <https://www.coin-or.org/Ipopt/documentation/node42.html> how
> this might be done. (dual_inf_tol?)
>
> Here is some output of a not-yet-converged optimization in case that is
> helpful. Each of my parameters is on the order of approximately -30 to +30
> and my constraints all have an upper bound of 1.0.
>
> This is Ipopt version 3.11.7, running with linear solver ma27.
>
> Number of nonzeros in equality constraint Jacobian...: 0
> Number of nonzeros in inequality constraint Jacobian.: 144
> Number of nonzeros in Lagrangian Hessian.............: 0
>
> Total number of variables............................: 12
> variables with only lower bounds: 0
> variables with lower and upper bounds: 12
> variables with only upper bounds: 0
> Total number of equality constraints.................: 0
> Total number of inequality constraints...............: 12
> inequality constraints with only lower bounds: 0
> inequality constraints with lower and upper bounds: 0
> inequality constraints with only upper bounds: 12
>
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 0 2.2773950e-10 4.72e-02 4.31e-01 0.0 0.00e+00 - 0.00e+00 0.00e+00 0
> 1 -4.9176078e-05 4.70e-02 9.91e-02 -4.8 9.65e-02 - 9.86e-01 1.00e+00h 1
> 2 2.1621729e-03 4.03e-02 1.12e-02 -2.8 8.31e-02 - 9.93e-01 1.00e+00h 1
> 3 2.4150351e-03 3.95e-02 7.40e-01 -3.3 5.27e-02 - 1.00e+00 1.86e-01h 1
> 4 1.3194689e-02 5.61e-03 3.60e-01 -3.4 4.16e-01 - 1.00e+00 1.00e+00h 1
> 5 1.4923797e-02 5.70e-04 2.12e+00 -4.8 7.84e-02 - 1.00e+00 1.00e+00h 1
> 6 1.1292725e-02 1.03e-02 6.11e-01 -4.3 1.28e-01 - 9.91e-01 1.00e+00h 1
> 7 -3.0932752e-02 1.78e-01 2.37e-02 -2.7 4.93e+01 - 9.77e-01 3.04e-02f 1
> 8 -1.0919263e-01 1.41e-01 1.83e-02 -3.7 6.55e+01 - 1.97e-01 2.13e-01h 1
> 9 -1.0200310e-02 6.29e-02 2.12e-01 -1.0 8.84e+02 - 1.91e-01 3.11e-02f 1
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 10 1.4379416e-02 7.83e-02 6.69e-02 -1.8 2.72e+01 - 5.78e-01 4.76e-01h 1
> 11 -6.2485434e-02 3.98e-02 4.35e-02 -1.8 2.23e+01 - 6.03e-01 1.00e+00h 1
> 12 -1.2862241e-01 1.22e-01 3.52e-03 -2.4 8.08e+00 - 1.00e+00 9.90e-01h 1
> 13 -1.4931148e-01 1.03e-01 1.28e-01 -3.5 7.31e+00 - 8.14e-01 1.00e+00h 1
> 14 -1.5628632e-01 1.73e-01 6.53e-02 -2.3 1.62e+01 - 1.00e+00 9.20e-01f 1
> 15 -1.4969877e-01 2.81e-02 5.75e-02 -2.4 1.44e+01 - 1.00e+00 9.86e-01h 1
> 16 -1.5014809e-01 1.13e-01 3.08e-02 -2.6 5.97e+00 - 9.57e-01 1.00e+00h 1
> 17 -1.5492389e-01 1.97e-02 6.94e+00 -3.3 3.98e+00 - 9.91e-01 1.00e+00h 1
> 18 -1.6660309e-01 5.33e-02 1.37e-02 -3.0 4.11e+00 - 9.90e-01 1.00e+00h 1
> 19 -1.6258901e-01 2.00e-01 7.76e-02 -2.7 5.95e+01 - 1.00e+00 1.72e-01h 2
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 20 -1.8526459e-01 3.63e-01 3.54e-02 -2.7 2.48e+01 - 4.07e-01 1.00e+00h 1
> 21 -1.7711436e-01 7.11e-02 1.58e-02 -3.1 1.31e+01 - 9.35e-01 1.00e+00h 1
> 22 -1.7548211e-01 4.64e-02 1.90e-01 -3.1 6.76e+00 - 5.89e-01 1.00e+00h 1
> 23 -1.8872718e-01 5.14e-01 5.11e-02 -2.7 8.01e+00 - 1.00e+00 9.03e-01h 1
> 24 -2.2657415e-01 1.51e+00 4.27e-03 -2.8 4.58e+01 - 4.16e-01 7.23e-01h 1
> 25 -2.1865212e-01 9.90e-01 1.52e+01 -2.8 1.94e+01 - 1.00e+00 4.04e-01h 1
> 26 -2.1865639e-01 9.90e-01 1.52e+01 -2.2 2.05e+01 - 9.93e-01 3.40e-04h 6
> 27 -2.1869343e-01 9.92e-01 1.51e+01 -3.3 2.94e+00 - 1.05e-02 1.05e-02s 16
> 28 -2.1869424e-01 9.91e-01 2.56e+05 -3.1 5.56e+00 - 1.00e+00 1.06e-04h 1
> 29r-2.1869424e-01 9.91e-01 6.51e+02 0.0 0.00e+00 - 0.00e+00 2.66e-07R 3
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 30r-2.1042636e-01 9.23e-01 1.85e+03 1.6 3.78e+02 - 1.00e+00 7.81e-04f 1
> 31 -2.1041707e-01 9.23e-01 8.99e+02 -4.8 1.50e+01 - 3.50e-01 3.85e-04h 1
> 32r-2.1041707e-01 9.23e-01 6.36e+02 1.2 0.00e+00 - 0.00e+00 4.82e-07R 4
> 33r-8.8862276e-03 4.97e-01 6.37e+02 3.1 1.26e+03 - 1.07e-02 6.68e-03f 1
> 34r-1.5970781e-02 5.08e-01 5.67e+02 1.4 1.32e+01 - 1.00e+00 4.22e-02f 1
> 35 8.0787130e-04 9.17e-03 8.87e+01 1.1 1.88e+02 - 4.69e-02 1.25e-01f 1
> 36 -2.3518550e-02 0.00e+00 1.37e+04 0.4 2.17e+00 - 3.97e-03 1.00e+00f 1
> 37 -1.8805455e-02 0.00e+00 1.11e+00 0.4 9.51e-01 - 1.00e+00 1.00e+00h 1
> 38 -1.7449909e-02 0.00e+00 3.81e-01 -0.3 1.72e+00 - 9.86e-01 1.00e+00f 1
> 39 -2.3978737e-02 0.00e+00 2.15e-02 -1.0 3.61e+00 - 1.00e+00 1.00e+00h 1
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 40 -2.4302684e-02 0.00e+00 1.38e-02 -3.1 3.49e-02 - 9.96e-01 1.00e+00h 1
> 41 -2.5007489e-02 0.00e+00 2.59e-02 -4.3 2.59e-02 - 9.97e-01 1.00e+00h 1
> 42 -2.5718840e-02 0.00e+00 2.61e-02 -5.9 2.61e-02 - 1.00e+00 1.00e+00h 1
> 43 -2.6430293e-02 0.00e+00 2.61e-02 -7.3 2.61e-02 - 1.00e+00 1.00e+00h 1
> 44 -7.4175847e-02 1.51e-02 2.61e-02 -5.3 2.96e+05 - 7.07e-06 5.89e-06f 1
> 45 -1.3141330e-01 1.27e-01 2.61e-02 -7.4 3.72e+05 - 2.02e-05 1.13e-05f 1
> 46 -1.5205276e-01 1.58e-01 2.61e-02 -7.4 2.22e+04 - 9.04e-04 1.16e-04f 1
> 47 -1.7484215e-01 2.50e-01 2.60e-02 -7.4 2.76e+04 - 8.48e-04 2.40e-04f 1
> 48 -1.8401410e-01 2.76e-01 2.60e-02 -7.4 3.18e+04 - 1.07e-03 6.43e-05f 1
> 49 -1.9843226e-01 3.54e-01 2.60e-02 -5.1 2.08e+04 - 1.65e-03 2.72e-04f 1
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 50 -2.1122735e-01 9.43e-01 2.60e-02 -5.2 2.08e+04 - 3.03e-03 4.51e-04f 1
> 51 -2.1122463e-01 9.43e-01 2.59e-02 -5.1 6.90e-01 - 6.08e-04 1.49e-04h 1
> 52 -1.7577586e-01 5.51e-01 1.67e-01 -5.8 1.34e+00 - 1.00e+00 1.00e+00h 1
> 53 -1.7055963e-01 5.20e-01 7.44e+00 -4.0 3.27e+00 - 2.92e-01 6.02e-02h 1
> 54 -7.0194072e-02 2.42e-01 5.35e+03 -4.0 3.62e+00 - 8.83e-02 1.00e+00h 1
> 55 -7.0281067e-02 2.43e-01 6.22e+00 -4.0 4.94e-02 - 4.30e-01 1.00e+00h 1
> 56 -7.0328967e-02 2.45e-01 2.62e-02 -4.0 2.02e-03 - 1.00e+00 1.00e+00h 1
> 57 -7.0328879e-02 2.45e-01 6.00e+00 -4.0 2.39e-01 - 1.00e+00 8.29e-05h 2
> 58 -6.6871118e-02 2.29e-01 4.76e+00 -4.0 4.28e+00 - 5.76e-02 6.70e-02h 1
> 59 -6.5418550e-02 2.23e-01 6.38e+00 -4.0 5.06e+00 - 1.00e+00 2.97e-02h 1
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 60 -6.1144197e-02 1.94e-01 5.06e+00 -4.0 5.21e+00 - 1.00e+00 1.09e-01h 1
> 61 -1.4374533e-01 6.24e-02 5.31e-01 -4.0 6.05e+00 - 1.32e-01 1.00e+00h 1
> 62 -1.9075327e-01 1.76e-01 1.15e-01 -4.0 1.56e+01 - 7.66e-01 1.80e-01h 1
> 63 -1.6009455e-01 1.04e-01 2.07e-02 -3.8 3.17e+00 - 1.00e+00 1.00e+00h 1
> 64 -1.6095612e-01 1.54e-01 4.94e-03 -2.8 6.40e+00 - 1.00e+00 1.00e+00f 1
> 65 -1.6644868e-01 1.13e-01 2.36e-02 -2.8 5.98e+00 - 1.00e+00 6.06e-01h 1
> 66 -1.7023044e-01 1.14e-01 1.87e-02 -2.8 7.48e+00 - 1.00e+00 1.00e+00h 1
> 67 -1.8720782e-01 1.65e-01 1.03e-03 -2.8 4.63e+00 - 1.00e+00 1.00e+00h 1
>
> I am fairly new to IPOPT so feel free to correct me if it is clear I am
> misunderstanding anything or if the optimization is obviously not
> performing well (I have my suspicions...)
> Thank you,
> Austin
>
>
>
>
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--
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