[Ipopt] Limited-memory quasi-newton option

[loerx]

Hi,

First of all: @ Andreas, Thank you very much for your comments! The 
derivative checker as well as the limited-memory bfgs option are working 
now.

Unfortunately, I ran into two new problems (questions).
1.) How can I stop ipopt if the objective is just below the 
primal_inf_tol (but not below the dual_inf_tol)? The 
acceptable_obj_change_tol option does not seem to work properly and I 
tried all the other options without success.

2.) Does anyone know why the objective jumps during the interation (see 
below)? (How can I circumvent this problem?) Is there any maximum step 
size implented in ipopt? Or might it be the restoration phase of the 
Hessian approximation.  (By the way, what does 1.00e+000w mean in the 
alpha_pr row? More precisely the w?)

Any help would be very nice!

Best regards,
Andre Loerx

PS: In my problems I consider a least squares formulation, such that the 
objective (and gradient) become(s) very small.

******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear 
optimization.
  Ipopt is released as open source code under the Common Public License 
(CPL).
          For more information visit http://projects.coin-or.org/Ipopt
******************************************************************************

This is Ipopt version 3.9.1, running with linear solver ma27.

No errors detected by derivative checker.

Number of nonzeros in equality constraint Jacobian...:        0
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:        0

Total number of variables............................:       16
                      variables with only lower bounds:        0
                 variables with lower and upper bounds:        0
                      variables with only upper bounds:        0
Total number of equality constraints.................:        0
Total number of inequality constraints...............:        0
         inequality constraints with only lower bounds:        0
    inequality constraints with lower and upper bounds:        0
         inequality constraints with only upper bounds:        0

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du 
alpha_pr  ls
    0 4.1541153e-002 0.00e+000 5.95e+001   0.0 0.00e+000    -  0.00e+000 
0.00e+000   0
    1 9.6285819e-003 0.00e+000 1.56e+001 -11.0 5.95e+001    -  1.00e+000 
9.77e-004f 11
    2 7.3407467e-003 0.00e+000 5.24e+000 -11.0 1.17e-002    -  1.00e+000 
1.00e+000f  1

...

   35 5.3918130e-005 0.00e+000 3.29e-001 -11.0 1.20e-001    -  1.00e+000 
1.25e-001f  4
   36 5.3046731e-005 0.00e+000 1.59e-001 -11.0 1.79e+000    -  1.00e+000 
3.91e-003f  9
   37 5.1043452e-005 0.00e+000 7.42e-002 -11.0 1.65e-001    -  1.00e+000 
1.25e-001f  4
   38 1.0373930e-003 0.00e+000 1.33e+000 -11.0 2.68e-001    -  1.00e+000 
1.00e+000w  1
   39 6.4342966e-004 0.00e+000 1.39e+000 -11.0 1.15e-001    -  1.00e+000 
1.00e+000w  1
   40 1.1531169e-002 0.00e+000 2.07e+001 -11.0 5.85e-001    -  1.00e+000 
1.00e+000w  1
   41 4.9804859e-005 0.00e+000 8.41e-002 -11.0 3.76e+000    -  1.00e+000 
6.25e-002f  4
   42 4.9566540e-005 0.00e+000 1.97e-001 -11.0 2.14e-001    -  1.00e+000 
3.13e-002f  6

...

   57 1.9789168e-005 0.00e+000 1.21e-001 -11.0 1.08e+001    -  1.00e+000 
9.77e-004f 11
   58 2.1811281e-003 0.00e+000 4.33e+000 -11.0 5.55e-001    -  1.00e+000 
1.00e+000w  1
   59 2.1245950e-002 0.00e+000 4.15e+001 -11.0 4.78e-001    -  1.00e+000 
1.00e+000w  1
   60 7.3051082e-003 0.00e+000 3.79e+000 -11.0 1.12e+000    -  1.00e+000 
1.00e+000w  1
   61 1.9132157e-005 0.00e+000 1.35e-001 -11.0 1.38e+000    -  1.00e+000 
6.25e-002f  4


...

                                   (scaled)                 (unscaled)
Objective...............:  2.4851902739530113e-009   2.4851902739530112e-011
Dual infeasibility......:  5.3455618178850871e-005   5.3455618178850870e-007
Constraint violation....:  0.0000000000000000e+000   0.0000000000000000e+000
Complementarity.........:  0.0000000000000000e+000   0.0000000000000000e+000
Overall NLP error.......:  5.3455618178850871e-005   5.3455618178850870e-007


Number of objective function evaluations             = 29513
Number of objective gradient evaluations             = 3001
Number of equality constraint evaluations            = 0
Number of inequality constraint evaluations          = 0
Number of equality constraint Jacobian evaluations   = 0
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations             = 0
Total CPU secs in IPOPT (w/o function evaluations)   =    179.341
Total CPU secs in NLP function evaluations           =  11448.251

...

-- 


+-- --- --- --- --- --- --- --- --- --- --- --- --+
Andre Loerx

University of Trier
FB IV - Department of Mathematics
54286 Trier, Germany

phone: +49 651 201 3468
fax:   +49 651 201 3973
email: loerx at uni-trier.de
www:   http://www.mathematik.uni-trier.de/~loerx
+-- --- --- --- --- --- --- --- --- --- --- --- --+

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