[Coin-ipopt] Question about time efficiency in really big problemand variable sensitive

[Su Ba]

Dear Andreas,

I am using Ipopt as a new hope for my really big problem of soil mechanics.  
Adapting your example (example.f),  I have already modelled my problem.  I 
met difficulty with memory allocation.  I have also read messages from 
Ipopt's mail-list. But I have many questions about it.  Could you explain 
them to me?

1.  Did you make any comparision of time between Ipopt and Lancelot in 
really big large-scale problem?  ( Your paper showed, the maximum variables 
is 125.000 variables)
   Variables:  960 000 + 640 000 slack variables
   Constraints:  640 000 (Inqualities in my problem is transformed)
   I used Lancelot, its solving time is not even practical in case of one 
half of the above problem.
   Up to now how many variables can Ipopt solve ?

2.  Adapting your sample example (example.f), I established gradient of 
constraints and Hessian of Lagrangian in "dense" way for problem of 162 
variables.  I used "imerit 4", "iquasi 6". It worked 2 times longer than 
Lancelot:  Ipopt 152s / Lancelot 21 s.  My computer's structure is AMD 64 
processor 3200, 512Mb.  Due to your mail-list, I am  now rewriting gradient 
of constraints and Hessian of Lagrangian in "sparse" way.  But I do not know 
if my "sparse" storage is correct:

For example:  Hessian of Lagragian in 5 variable problem:

a
0    b
0    0     c
0    d     0     e
f     0     0     0     g

Then:
K = / 1   2   3  4  5  6  7/  or K = /1  3   6   8  10  11 15/  is correct?
HESS(K)= / a   b   c   d   e  f   g/
IRNH(K)= / 1   2   3   4   4  5   5/
ICNH(K)= / 1   2   3   2   4  1   5/

In your example, it is clear that you used K in the second way.  If it is 
true, it turns out that total number of HESS in "sparse" way and "dense" way 
are equal due to declaration of static array.

3.  About the termination of the problem, it is proved that my 
differentiable convex optimization has always a solution.  By using 
Lancelot, I got the solution.  But Ipopt stopped with IERR=1, it means I 
must increase IMAXITER.  However the solution of final step is acceptable 
(means it is approximately to Lancelot's one).

My PARAM.DAT is as follows:
dtol = 1d-4
imerit = 4  (as default)
iquasi = 6
iprint =1
ifile = 1
ioutput = 1
imaxiter = 10000

If I had increased "maxiter", IERR was always 1.  I saw a vibration of 
solution in range of 1d-1.  But If I  had made choice of dtol=1d-1.  Ipopt 
sttoped at point very far from my Lancelot's solution.  Please show me how 
to avoid IERR=1.  Lancelot use Augemented Lagrange method. So muss I change 
any parameters?  (Parameters in Ipopt are too much for me to understand all 
!)

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