The issue seems to be somehow related to the length of the problem. I
can get the problem to the point where it just works (by editing out
part of the problem text), and then when I append a " + 1" the problem
fails.
The problem only has 14 variables with no constraints (I took them
out), but it is rather long -- 3,796,374 bytes for the objective
function.
I'm having the same problem with both IPOPT and Minos, although the
issue does not seem to be with the solver (AMPL crashes *before* the
solver message (e.g., "Ipopt 3.2.3:") appears.
Any help would be greatly appreciated.
JACOB.
Try setting "option gentimes 1" to get more detailed output concerning AMPL's
progress. (For further explanation of this option see the discussion in
question 3.6 at www.ampl.com/FAQ.)
Any crash is by definition a bug, though. So unless your problem magically
goes away, you should send your files to in...@ampl.com so that they can be run
on the latest version of AMPL and a bug fix can be made if necessary.
Bob Fourer
4...@ampl.com
On Apr 6, 3:47 pm, "Robert Fourer" <4...@ampl.com> wrote:
> Try setting "option gentimes 1" to get more detailed output concerning AMPL's
> progress. (For further explanation of this option see the discussion in
> question 3.6 atwww.ampl.com/FAQ.)
I just have that a try. I also added 'option times 1;' and 'option
show_stats 1;' for good measure.
Output as follows:
C:\amplcml>ampl.exe
ampl: model foo.mod;
# incremental total
#phase seconds memory memory
#execute 0.015625 206868 206872
### foo.mod:4(44) option ...
#execute 0 0 206872
### foo.mod:5(63) option ...
#execute 0 0 206872
### foo.mod:16421(2847148) solve ...
C:\amplcml>
> Any crash is by definition a bug, though. So unless your problem magically
> goes away, you should send your files to i...@ampl.com so that they can be run
> on the latest version of AMPL and a bug fix can be made if necessary.
Sounds about right. I just want to make sure the problem's not my own.
Wouldn't be the first time I've screwed something up.
A simplified version of my objective function is a linear combination
of logarithms with each log term looking something like this:
1.39628860198736e-005 * log( 1 + -1 * x1 + -1 * x2 + -1 * x3 + -1 * x4
+ -1 * x5 + -1 * x6 + -1 * x7 + -1 * x8 + -1 * x9 + -1 * x10 + -1 *
x11 + -1 * x12 + -1 * x13 + -1 * x14 )
Within each log term every combination of the 14 x1 ... x14 decision
variables with coefficients of +1 and -1 are summed together (2^14
16,384 terms). So one term would be as above, another term would be
identical but with a +1 as coefficient to x1, etc.